- Detection si Jean/Ollama inaccessible - Envoi magic packet WoL vers TARGET_MAC (fallback PC_GAMING_MAC) - Attente WAKE_TIMEOUT secondes que la machine demarre - Integration dans get_presets, get_ollama_models, chat_completions - Verrous pour eviter les WoL simultanes - Active via ENABLE_WOL=true
887 lines
30 KiB
Python
887 lines
30 KiB
Python
#!/usr/bin/env python3
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"""
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Jean Router — Proxy dynamique pour Jean presets
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Interroge Jean pour lister les presets disponibles et route les requêtes
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vers le bon preset en faisant le switch automatique si nécessaire.
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"""
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import os
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import time
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import logging
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import threading
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import socket
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from typing import Optional
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import requests
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from flask import Flask, request, Response, jsonify
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JEAN_WEB_HOST = os.getenv("JEAN_WEB_HOST", "192.168.1.11")
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JEAN_WEB_PORT = int(os.getenv("JEAN_WEB_PORT", "8090"))
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JEAN_PROXY_HOST = os.getenv("JEAN_PROXY_HOST", "localhost")
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JEAN_PROXY_PORT = int(os.getenv("JEAN_PROXY_PORT", "3012"))
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OLLAMA_PROXY_HOST = os.getenv("OLLAMA_PROXY_HOST", "localhost")
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OLLAMA_PROXY_PORT = int(os.getenv("OLLAMA_PROXY_PORT", "3011"))
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OLLAMA_DIRECT_HOST = os.getenv("OLLAMA_DIRECT_HOST", JEAN_WEB_HOST)
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OLLAMA_DIRECT_PORT = int(os.getenv("OLLAMA_DIRECT_PORT", "11434"))
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ENABLE_OLLAMA = os.getenv("ENABLE_OLLAMA", "true").lower() == "true"
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ENABLE_VRAM_MANAGEMENT = os.getenv("ENABLE_VRAM_MANAGEMENT", "true").lower() == "true"
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OLLAMA_KEEP_ALIVE_MINUTES = int(os.getenv("OLLAMA_KEEP_ALIVE_MINUTES", "5"))
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LISTEN_PORT = int(os.getenv("LISTEN_PORT", "3014"))
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SWITCH_TIMEOUT = int(os.getenv("SWITCH_TIMEOUT", "90"))
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CHECK_INTERVAL = int(os.getenv("CHECK_INTERVAL", "2"))
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JEAN_STOP_TIMEOUT = int(os.getenv("JEAN_STOP_TIMEOUT", "30"))
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OLLAMA_UNLOAD_TIMEOUT = int(os.getenv("OLLAMA_UNLOAD_TIMEOUT", "15"))
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ENABLE_WOL = os.getenv("ENABLE_WOL", "false").lower() == "true"
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TARGET_MAC = os.getenv("TARGET_MAC", os.getenv("PC_GAMING_MAC", ""))
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BROADCAST_IP = os.getenv("BROADCAST_IP", "192.168.1.255")
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WAKE_TIMEOUT = int(os.getenv("WAKE_TIMEOUT", "120"))
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wol_in_progress = threading.Lock()
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jean_alive_cache = {"alive": False, "timestamp": 0}
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logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
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log = logging.getLogger(__name__)
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app = Flask(__name__)
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presets_cache = {"data": [], "timestamp": 0}
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ollama_cache = {"data": [], "timestamp": 0}
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ollama_detail_cache = {}
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jean_ctx_cache = {}
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jean_caps_cache = {}
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CACHE_TTL = int(os.getenv("CACHE_TTL", "15"))
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OLLAMA_DETAIL_CACHE_TTL = 300
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switch_lock = threading.Lock()
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vram_lock = threading.Lock()
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vram_state = {"active_backend": "jean"}
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last_active_preset = None
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ollama_unload_timer = None
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def get_presets(force_refresh=False):
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"""Récupère la liste des presets depuis Jean"""
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now = time.time()
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if not force_refresh and presets_cache["data"] and (now - presets_cache["timestamp"]) < CACHE_TTL:
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return presets_cache["data"]
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try:
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url = f"http://{JEAN_WEB_HOST}:{JEAN_WEB_PORT}/api/presets"
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r = requests.get(url, timeout=3)
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if r.ok:
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presets_cache["data"] = r.json()
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presets_cache["timestamp"] = now
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return presets_cache["data"]
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except Exception as e:
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log.warning(f"[Presets] Erreur récupération: {e}")
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if ENABLE_WOL and (not presets_cache["data"] or force_refresh):
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wait_for_jean(trigger_wol=True)
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try:
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r = requests.get(f"http://{JEAN_WEB_HOST}:{JEAN_WEB_PORT}/api/presets", timeout=5)
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if r.ok:
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presets_cache["data"] = r.json()
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presets_cache["timestamp"] = now
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return presets_cache["data"]
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except Exception:
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pass
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return presets_cache["data"]
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def send_wol():
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"""Envoie un magic packet WoL vers TARGET_MAC"""
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if not TARGET_MAC:
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log.warning("[WoL] TARGET_MAC non defini, WoL desactive")
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return
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mac = TARGET_MAC.replace(":", "").replace("-", "")
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if len(mac) != 12:
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log.error(f"[WoL] MAC invalide: {TARGET_MAC}")
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return
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data = bytes.fromhex("FF" * 6 + mac * 16)
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with socket.socket(socket.AF_INET, socket.SOCK_DGRAM) as s:
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s.setsockopt(socket.SOL_SOCKET, socket.SO_BROADCAST, 1)
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for i in range(3):
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s.sendto(data, (BROADCAST_IP, 9))
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log.info(f"[WoL] Magic packet #{i+1} envoye vers {TARGET_MAC}")
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def jean_alive() -> bool:
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"""Verifie si Jean est accessible"""
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now = time.time()
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if now - jean_alive_cache["timestamp"] < 5:
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return jean_alive_cache["alive"]
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try:
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url = f"http://{JEAN_WEB_HOST}:{JEAN_WEB_PORT}/api/presets"
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r = requests.get(url, timeout=3)
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alive = r.ok
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except Exception:
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alive = False
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jean_alive_cache["alive"] = alive
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jean_alive_cache["timestamp"] = now
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return alive
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def wait_for_jean(trigger_wol=True):
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"""Attend que Jean soit accessible. Si ENABLE_WOL et trigger_wol, envoie WoL d'abord."""
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if jean_alive():
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return
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if not ENABLE_WOL or not trigger_wol:
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return
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with wol_in_progress:
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if jean_alive():
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return
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log.info("[WoL] Jean inaccessible, envoi WoL...")
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send_wol()
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deadline = time.time() + WAKE_TIMEOUT
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while time.time() < deadline:
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if jean_alive():
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jean_alive_cache["timestamp"] = 0
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log.info(f"[WoL] Jean UP apres {int(time.time() - deadline + WAKE_TIMEOUT)}s")
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return
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time.sleep(CHECK_INTERVAL)
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log.error(f"[WoL] Jean ne repond pas apres {WAKE_TIMEOUT}s")
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def get_ollama_models(force_refresh=False):
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"""Récupère la liste des modèles depuis Ollama"""
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if not ENABLE_OLLAMA:
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return []
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now = time.time()
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if not force_refresh and ollama_cache["data"] and (now - ollama_cache["timestamp"]) < CACHE_TTL:
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return ollama_cache["data"]
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try:
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url = f"http://{OLLAMA_PROXY_HOST}:{OLLAMA_PROXY_PORT}/api/tags"
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r = requests.get(url, timeout=3)
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if r.ok:
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data = r.json().get("models", [])
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ollama_cache["data"] = data
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ollama_cache["timestamp"] = now
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return data
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except Exception as e:
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log.warning(f"[Ollama] Erreur récupération: {e}")
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if ENABLE_WOL and (not ollama_cache["data"] or force_refresh):
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wait_for_jean(trigger_wol=True)
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try:
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r = requests.get(f"http://{OLLAMA_PROXY_HOST}:{OLLAMA_PROXY_PORT}/api/tags", timeout=5)
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if r.ok:
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data = r.json().get("models", [])
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ollama_cache["data"] = data
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ollama_cache["timestamp"] = now
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return data
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except Exception:
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pass
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return ollama_cache["data"]
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def _get_ollama_model_detail(model_name: str) -> dict:
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"""Récupère les détails d'un modèle Ollama via /api/show, avec cache long"""
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now = time.time()
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cached = ollama_detail_cache.get(model_name)
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if cached and (now - cached["timestamp"]) < OLLAMA_DETAIL_CACHE_TTL:
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return cached["data"]
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detail = {}
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try:
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clean_name = model_name.replace(":latest", "")
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url = f"http://{OLLAMA_DIRECT_HOST}:{OLLAMA_DIRECT_PORT}/api/show"
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r = requests.post(url, json={"model": clean_name}, timeout=10)
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if r.ok:
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d = r.json()
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model_info = d.get("model_info", {})
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details = d.get("details", {})
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for key, val in model_info.items():
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if "context_length" in key.lower() or "ctx" in key.lower():
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detail["context_length"] = int(val)
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break
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if not detail.get("context_length"):
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detail["context_length"] = details.get("context_length")
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detail["capabilities"] = d.get("capabilities", [])
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detail["family"] = details.get("family", "")
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ollama_detail_cache[model_name] = {"data": detail, "timestamp": now}
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except Exception as e:
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log.debug(f"[Ollama] /api/show echoue pour {model_name}: {e}")
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if model_name not in ollama_detail_cache:
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ollama_detail_cache[model_name] = {"data": {}, "timestamp": now}
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return ollama_detail_cache[model_name]["data"]
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def _enrich_ollama_model(m: dict) -> dict:
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"""Enrichit un modele Ollama avec les donnees /api/show si necessaire"""
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model_id = m.get("name", "").replace(":latest", "")
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details = m.get("details", {})
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has_ctx = bool(details.get("context_length"))
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caps = m.get("capabilities", [])
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if not has_ctx or len(caps) <= 1:
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extra = _get_ollama_model_detail(model_id)
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if extra.get("context_length"):
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details = dict(details)
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details["context_length"] = extra["context_length"]
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m = dict(m)
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m["details"] = details
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if extra.get("capabilities") and len(extra["capabilities"]) > len(caps):
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m = dict(m)
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m["capabilities"] = extra["capabilities"]
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if extra.get("family") and not details.get("family"):
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details = dict(details)
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details["family"] = extra["family"]
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m = dict(m)
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m["details"] = details
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return m
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def _guess_context_length(preset_id: str) -> int:
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"""Devine le context_length depuis le nom du preset"""
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pid = preset_id.lower()
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if "qwen3.6" in pid or "qwen3.5" in pid:
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return 262144
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if "qwen3" in pid:
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return 40960
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if "qwen2.5" in pid:
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return 32768
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if "mistral" in pid or "nemo" in pid:
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return 1024000
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if "llama" in pid:
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return 131072
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if "ornith" in pid:
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return 131072
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if "gemma" in pid:
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return 262144
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if "deepseek" in pid:
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return 131072
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if "phi" in pid:
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return 16384
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if "35b" in pid or "27b" in pid:
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return 131072
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return 32768
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def _guess_capabilities(preset_id: str) -> list:
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"""Devine les capabilities depuis le nom du preset + metadonnees Jean"""
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pid = preset_id.lower()
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caps = ["completion"]
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has_vision = any(kw in pid for kw in ["vision", "vl", "llava", "bakllava", "minicpm"])
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has_thinking = any(kw in pid for kw in ["reason", "thinking", "deepseek-r1"])
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has_tools = not any(kw in pid for kw in ["embed", "bge-", "nomic-"])
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if has_vision:
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caps.append("vision")
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if has_thinking:
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caps.append("thinking")
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if has_tools:
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caps.append("tools")
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return caps
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def _match_preset_to_ollama(preset_id: str):
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"""Tente de trouver un modele Ollama correspondant au preset Jean"""
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ollama_models = get_ollama_models()
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pid_lower = preset_id.lower()
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def norm(s):
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return s.lower().replace(":", "").replace("-", "").replace(" ", "").replace(".", "")
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pid_norm = norm(pid_lower)
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for m in ollama_models:
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name = m.get("name", "").replace(":latest", "")
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name_norm = norm(name)
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if pid_norm == name_norm:
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return m
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best = None
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best_score = 0
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for m in ollama_models:
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name = m.get("name", "").replace(":latest", "")
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name_norm = norm(name)
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score = 0
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if len(pid_norm) >= 4 and pid_norm[:4] == name_norm[:4]:
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score += 10
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if len(pid_norm) >= 8 and pid_norm[:8] == name_norm[:8]:
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score += 20
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if name_norm in pid_norm or pid_norm in name_norm:
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score += 15
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parts_pid = set(pid_norm.split("_"))
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parts_name = set(name_norm.split("_"))
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common = parts_pid & parts_name
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score += len(common) * 5
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if score > best_score:
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best_score = score
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best = m
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if best and best_score >= 5:
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return best
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return None
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def get_jean_metadata():
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"""Resout dynamiquement context_length et capabilities pour les presets Jean.
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1) Ollama matching → 2) Jean /v1/models → 3) heuristique"""
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now = time.time()
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try:
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url = f"http://{JEAN_PROXY_HOST}:{JEAN_PROXY_PORT}/v1/models"
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r = requests.get(url, timeout=2)
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if r.ok:
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for m in r.json().get("data", []):
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alias = m.get("id", "")
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meta = m.get("meta", {})
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n_ctx = meta.get("n_ctx") or m.get("max_model_len")
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if n_ctx and alias:
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jean_ctx_cache[alias] = int(n_ctx)
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except Exception:
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pass
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ollama_models = get_ollama_models()
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ollama_lookup = {}
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for m in ollama_models:
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m = _enrich_ollama_model(m)
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name = m.get("name", "").replace(":latest", "")
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details = m.get("details", {})
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ctx = details.get("context_length")
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caps = m.get("capabilities", [])
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ollama_lookup[name] = {"context_length": ctx, "capabilities": caps}
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presets = get_presets()
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for p in presets:
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pid = p["id"]
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matched_ollama = _match_preset_to_ollama(pid)
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ollama_name = matched_ollama.get("name", "").replace(":latest", "") if matched_ollama else None
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if pid not in jean_ctx_cache:
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if ollama_name and ollama_lookup.get(ollama_name, {}).get("context_length"):
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jean_ctx_cache[pid] = ollama_lookup[ollama_name]["context_length"]
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else:
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jean_ctx_cache[pid] = _guess_context_length(pid)
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if pid not in jean_caps_cache:
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if p.get("reasoning") == "on":
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caps = ["completion", "tools", "thinking"]
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else:
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caps = ["completion", "tools"]
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if ollama_name and ollama_lookup.get(ollama_name, {}).get("capabilities"):
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ollama_caps = ollama_lookup[ollama_name]["capabilities"]
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caps = list(dict.fromkeys(caps + ollama_caps))
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jean_caps_cache[pid] = caps
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return jean_ctx_cache, jean_caps_cache
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def get_active_preset():
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"""Retourne le preset actuellement actif"""
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presets = get_presets()
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for p in presets:
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if p.get("active"):
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return p
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return None
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def switch_preset(preset_id: str) -> bool:
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"""Switch vers un preset spécifique par son ID"""
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global last_active_preset
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presets = get_presets(force_refresh=True)
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for i, p in enumerate(presets):
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if p["id"] == preset_id:
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if p.get("active"):
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log.info(f"[Switch] Preset {preset_id} déjà actif")
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return True
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log.info(f"[Switch] Activation preset {preset_id} (index {i+1})")
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success = False
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for attempt in range(2):
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try:
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url = f"http://{JEAN_WEB_HOST}:{JEAN_WEB_PORT}/api/switch"
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r = requests.post(url, json={"n": i + 1}, timeout=15)
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if r.ok:
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success = True
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break
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log.error(f"[Switch] Erreur API (tentative {attempt+1}): {r.text}")
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except Exception as e:
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log.error(f"[Switch] Erreur requête (tentative {attempt+1}): {e}")
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if attempt == 0:
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time.sleep(3)
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if not success:
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return False
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log.info(f"[Switch] Attente chargement modèle...")
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deadline = time.time() + SWITCH_TIMEOUT
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while time.time() < deadline:
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try:
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health_url = f"http://{JEAN_PROXY_HOST}:{JEAN_PROXY_PORT}/health"
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hr = requests.get(health_url, timeout=2)
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if hr.ok:
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models_url = f"http://{JEAN_PROXY_HOST}:{JEAN_PROXY_PORT}/v1/models"
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mr = requests.get(models_url, timeout=2)
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if mr.ok:
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models = mr.json().get("data", [])
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if models:
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log.info(f"[Switch] Modèle chargé après {int(time.time() - deadline + SWITCH_TIMEOUT)}s")
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last_active_preset = preset_id
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presets_cache["timestamp"] = 0
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return True
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except Exception:
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pass
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time.sleep(CHECK_INTERVAL)
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log.error(f"[Switch] Timeout après {SWITCH_TIMEOUT}s")
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return False
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log.error(f"[Switch] Preset {preset_id} non trouvé")
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return False
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def stop_jean() -> bool:
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"""Arrête le service Jean pour libérer la VRAM"""
|
|
log.info("[VRAM] Arrêt de Jean pour libérer la VRAM...")
|
|
|
|
try:
|
|
url = f"http://{JEAN_WEB_HOST}:{JEAN_WEB_PORT}/api/stop"
|
|
r = requests.post(url, timeout=5)
|
|
if r.ok:
|
|
log.info("[VRAM] Jean arrêté via API web")
|
|
else:
|
|
log.warning(f"[VRAM] API stop a retourné {r.status_code}, tentative via health check")
|
|
except Exception as e:
|
|
log.warning(f"[VRAM] Erreur API stop: {e}")
|
|
|
|
deadline = time.time() + JEAN_STOP_TIMEOUT
|
|
while time.time() < deadline:
|
|
try:
|
|
health_url = f"http://{JEAN_WEB_HOST}:{JEAN_WEB_PORT}/health"
|
|
r = requests.get(health_url, timeout=2)
|
|
if not r.ok:
|
|
log.info("[VRAM] Jean confirmé arrêté")
|
|
return True
|
|
except Exception:
|
|
log.info("[VRAM] Jean confirmé arrêté (connexion refusée)")
|
|
return True
|
|
time.sleep(CHECK_INTERVAL)
|
|
|
|
log.error(f"[VRAM] Timeout: Jean ne s'est pas arrêté après {JEAN_STOP_TIMEOUT}s")
|
|
return False
|
|
|
|
|
|
def start_jean() -> bool:
|
|
"""Démarre le service Jean"""
|
|
log.info("[VRAM] Démarrage de Jean...")
|
|
|
|
try:
|
|
url = f"http://{JEAN_WEB_HOST}:{JEAN_WEB_PORT}/api/start"
|
|
r = requests.post(url, timeout=5)
|
|
if r.ok:
|
|
log.info("[VRAM] Jean démarré via API web")
|
|
else:
|
|
log.warning(f"[VRAM] API start a retourné {r.status_code}")
|
|
except Exception as e:
|
|
log.warning(f"[VRAM] Erreur API start: {e}")
|
|
|
|
log.info("[VRAM] Attente du chargement du modèle Jean...")
|
|
deadline = time.time() + SWITCH_TIMEOUT
|
|
while time.time() < deadline:
|
|
try:
|
|
health_url = f"http://{JEAN_PROXY_HOST}:{JEAN_PROXY_PORT}/health"
|
|
hr = requests.get(health_url, timeout=2)
|
|
if hr.ok:
|
|
models_url = f"http://{JEAN_PROXY_HOST}:{JEAN_PROXY_PORT}/v1/models"
|
|
mr = requests.get(models_url, timeout=2)
|
|
if mr.ok:
|
|
models = mr.json().get("data", [])
|
|
if models:
|
|
log.info(f"[VRAM] Jean prêt après {int(time.time() - deadline + SWITCH_TIMEOUT)}s")
|
|
return True
|
|
except Exception:
|
|
pass
|
|
time.sleep(CHECK_INTERVAL)
|
|
|
|
log.error(f"[VRAM] Timeout: Jean n'a pas démarré après {SWITCH_TIMEOUT}s")
|
|
return False
|
|
|
|
|
|
def unload_ollama() -> bool:
|
|
"""Force le déchargement des modèles Ollama pour libérer la VRAM"""
|
|
log.info("[VRAM] Déchargement des modèles Ollama...")
|
|
|
|
try:
|
|
url = f"http://{OLLAMA_DIRECT_HOST}:{OLLAMA_DIRECT_PORT}/api/generate"
|
|
payload = {
|
|
"model": "mistral",
|
|
"keep_alive": 0,
|
|
"prompt": ""
|
|
}
|
|
r = requests.post(url, json=payload, timeout=5)
|
|
if r.ok:
|
|
log.info("[VRAM] Ollama déchargé via API")
|
|
return True
|
|
else:
|
|
log.warning(f"[VRAM] API unload a retourné {r.status_code}")
|
|
except Exception as e:
|
|
log.warning(f"[VRAM] Erreur API unload: {e}")
|
|
|
|
try:
|
|
url = f"http://{OLLAMA_DIRECT_HOST}:{OLLAMA_DIRECT_PORT}/api/ps"
|
|
r = requests.get(url, timeout=3)
|
|
if r.ok:
|
|
models = r.json().get("models", [])
|
|
if not models:
|
|
log.info("[VRAM] Ollama confirmé déchargé (aucun modèle actif)")
|
|
return True
|
|
else:
|
|
log.warning(f"[VRAM] Ollama a encore {len(models)} modèle(s) chargé(s)")
|
|
except Exception as e:
|
|
log.warning(f"[VRAM] Impossible de vérifier /api/ps: {e}")
|
|
|
|
time.sleep(2)
|
|
log.info("[VRAM] Ollama supposé déchargé (timeout)")
|
|
return True
|
|
|
|
|
|
def schedule_ollama_unload():
|
|
"""Programme le déchargement d'Ollama après OLLAMA_KEEP_ALIVE_MINUTES"""
|
|
global ollama_unload_timer
|
|
|
|
def delayed_unload():
|
|
log.info(f"[VRAM] Timer écoulé ({OLLAMA_KEEP_ALIVE_MINUTES}min), déchargement Ollama...")
|
|
unload_ollama()
|
|
|
|
if ollama_unload_timer:
|
|
ollama_unload_timer.cancel()
|
|
log.info("[VRAM] Timer précédent annulé")
|
|
|
|
ollama_unload_timer = threading.Timer(
|
|
OLLAMA_KEEP_ALIVE_MINUTES * 60,
|
|
delayed_unload
|
|
)
|
|
ollama_unload_timer.daemon = True
|
|
ollama_unload_timer.start()
|
|
log.info(f"[VRAM] Déchargement Ollama programmé dans {OLLAMA_KEEP_ALIVE_MINUTES} minutes")
|
|
|
|
|
|
def cancel_ollama_unload():
|
|
"""Annule le déchargement programmé d'Ollama"""
|
|
global ollama_unload_timer
|
|
if ollama_unload_timer:
|
|
ollama_unload_timer.cancel()
|
|
ollama_unload_timer = None
|
|
log.info("[VRAM] Timer de déchargement Ollama annulé")
|
|
|
|
|
|
def ensure_vram_for_backend(target_backend: str) -> bool:
|
|
"""
|
|
S'assure que la VRAM est disponible pour le backend cible.
|
|
- Si target=ollama et jean actif → arrête Jean, annule timer unload Ollama
|
|
- Si target=jean et ollama actif → programme déchargement Ollama dans X min, démarre Jean
|
|
"""
|
|
if not ENABLE_VRAM_MANAGEMENT:
|
|
return True
|
|
|
|
global last_active_preset
|
|
|
|
with vram_lock:
|
|
current = vram_state["active_backend"]
|
|
|
|
if current == target_backend:
|
|
return True
|
|
|
|
if target_backend == "ollama" and current == "jean":
|
|
log.info("[VRAM] Switch Jean → Ollama")
|
|
cancel_ollama_unload()
|
|
if not stop_jean():
|
|
return False
|
|
last_active_preset = None
|
|
vram_state["active_backend"] = "ollama"
|
|
return True
|
|
|
|
elif target_backend == "jean" and current == "ollama":
|
|
log.info("[VRAM] Switch Ollama → Jean")
|
|
schedule_ollama_unload()
|
|
if not start_jean():
|
|
return False
|
|
last_active_preset = None
|
|
vram_state["active_backend"] = "jean"
|
|
return True
|
|
|
|
return True
|
|
|
|
|
|
@app.route("/v1/models", methods=["GET"])
|
|
def list_models():
|
|
"""Expose tous les presets Jean + modèles Ollama comme modèles OpenAI"""
|
|
force_refresh = request.args.get("refresh", "").lower() in ("1", "true", "yes")
|
|
if force_refresh:
|
|
global presets_cache, ollama_cache
|
|
presets_cache["timestamp"] = 0
|
|
ollama_cache["timestamp"] = 0
|
|
log.info("[Models] Refresh force demande")
|
|
|
|
presets = get_presets()
|
|
jean_ctx, jean_caps = get_jean_metadata()
|
|
models = []
|
|
|
|
for p in presets:
|
|
model_id = p["id"]
|
|
model_name = p.get("name", model_id)
|
|
|
|
ctx_len = jean_ctx.get(model_id)
|
|
caps = jean_caps.get(model_id, ["completion", "tools"])
|
|
if p.get("reasoning") == "on" and "thinking" not in caps:
|
|
caps = list(dict.fromkeys(caps + ["thinking"]))
|
|
|
|
model_info = {
|
|
"id": model_name,
|
|
"object": "model",
|
|
"created": int(time.time()),
|
|
"owned_by": "jean",
|
|
"permission": [],
|
|
"root": model_name,
|
|
"parent": None,
|
|
}
|
|
|
|
if ctx_len:
|
|
model_info["context_length"] = ctx_len
|
|
model_info["context_window"] = ctx_len
|
|
model_info["max_model_len"] = ctx_len
|
|
model_info["max_tokens"] = ctx_len
|
|
model_info["max_input_tokens"] = ctx_len
|
|
|
|
model_info["capabilities"] = caps
|
|
|
|
meta = {}
|
|
if p.get("name") and p["name"] != model_id:
|
|
meta["display_name"] = p["name"]
|
|
if p.get("quant"):
|
|
meta["quantization"] = p["quant"]
|
|
if p.get("reasoning"):
|
|
meta["reasoning"] = p["reasoning"]
|
|
if p.get("active"):
|
|
meta["active"] = True
|
|
if p.get("bench"):
|
|
meta["bench"] = p["bench"]
|
|
if ctx_len:
|
|
meta["context_length"] = ctx_len
|
|
meta["capabilities"] = caps
|
|
|
|
if meta:
|
|
model_info["meta"] = meta
|
|
|
|
models.append(model_info)
|
|
|
|
if ENABLE_OLLAMA:
|
|
ollama_models = get_ollama_models()
|
|
for m in ollama_models:
|
|
m = _enrich_ollama_model(m)
|
|
model_id = m.get("name", "").replace(":latest", "")
|
|
if not model_id:
|
|
continue
|
|
|
|
caps = m.get("capabilities", ["completion"])
|
|
details = m.get("details", {})
|
|
ctx_len = details.get("context_length")
|
|
|
|
model_info = {
|
|
"id": model_id,
|
|
"object": "model",
|
|
"created": int(time.time()),
|
|
"owned_by": "ollama",
|
|
"permission": [],
|
|
"root": model_id,
|
|
"parent": None,
|
|
}
|
|
|
|
if ctx_len:
|
|
model_info["context_length"] = ctx_len
|
|
model_info["context_window"] = ctx_len
|
|
model_info["max_model_len"] = ctx_len
|
|
model_info["max_tokens"] = ctx_len
|
|
model_info["max_input_tokens"] = ctx_len
|
|
|
|
model_info["capabilities"] = caps
|
|
|
|
meta = {}
|
|
if details.get("parameter_size"):
|
|
meta["parameter_size"] = details["parameter_size"]
|
|
if details.get("quantization_level"):
|
|
meta["quantization"] = details["quantization_level"]
|
|
if details.get("family"):
|
|
meta["family"] = details["family"]
|
|
if ctx_len:
|
|
meta["context_length"] = ctx_len
|
|
meta["capabilities"] = caps
|
|
|
|
if meta:
|
|
model_info["meta"] = meta
|
|
|
|
models.append(model_info)
|
|
|
|
return jsonify({"object": "list", "data": models})
|
|
|
|
|
|
@app.route("/v1/chat/completions", methods=["POST"])
|
|
def chat_completions():
|
|
"""Route les requêtes chat vers Jean ou Ollama selon le modèle"""
|
|
data = request.get_json()
|
|
model_id = data.get("model")
|
|
|
|
if not model_id:
|
|
return jsonify({"error": "model parameter required"}), 400
|
|
|
|
presets = get_presets()
|
|
jean_preset_ids = {p["id"] for p in presets}
|
|
jean_name_to_id = {p.get("name", p["id"]): p["id"] for p in presets}
|
|
jean_names = set(jean_name_to_id.keys())
|
|
|
|
if model_id in jean_preset_ids or model_id in jean_names:
|
|
internal_id = jean_name_to_id.get(model_id, model_id)
|
|
|
|
wait_for_jean(trigger_wol=True)
|
|
|
|
if not ensure_vram_for_backend("jean"):
|
|
return jsonify({"error": "Failed to prepare VRAM for Jean"}), 503
|
|
|
|
with switch_lock:
|
|
active = get_active_preset()
|
|
current_active = active["id"] if active else last_active_preset
|
|
if current_active != internal_id:
|
|
log.info(f"[Router] Switch Jean requis: {current_active or 'none'} → {internal_id} ({model_id})")
|
|
if not switch_preset(internal_id):
|
|
return jsonify({"error": f"Failed to switch to preset {model_id}"}), 503
|
|
else:
|
|
log.info(f"[Router] Preset {model_id} déjà actif (tracké)")
|
|
|
|
preset = next((p for p in presets if p["id"] == internal_id), {})
|
|
if preset.get("reasoning") == "on":
|
|
ctx, _ = get_jean_metadata()
|
|
ctx_len = ctx.get(internal_id, 131072)
|
|
req_max = data.get("max_tokens", 0)
|
|
if req_max and req_max > 0:
|
|
new_max = min(req_max * 2, ctx_len)
|
|
if new_max != req_max:
|
|
log.info(f"[Reasoning] max_tokens doublé: {req_max} → {new_max}")
|
|
data = dict(data)
|
|
data["max_tokens"] = new_max
|
|
|
|
upstream_url = f"http://{JEAN_PROXY_HOST}:{JEAN_PROXY_PORT}/v1/chat/completions"
|
|
log.info(f"[Router] → Jean ({model_id})")
|
|
elif ENABLE_OLLAMA:
|
|
wait_for_jean(trigger_wol=True)
|
|
ollama_models = get_ollama_models()
|
|
ollama_ids = [m.get("name", "").replace(":latest", "") for m in ollama_models]
|
|
|
|
if model_id in ollama_ids:
|
|
if not ensure_vram_for_backend("ollama"):
|
|
return jsonify({"error": "Failed to prepare VRAM for Ollama"}), 503
|
|
|
|
cancel_ollama_unload()
|
|
|
|
upstream_url = f"http://{OLLAMA_PROXY_HOST}:{OLLAMA_PROXY_PORT}/v1/chat/completions"
|
|
log.info(f"[Router] → Ollama ({model_id})")
|
|
else:
|
|
return jsonify({"error": f"Unknown model: {model_id}"}), 404
|
|
else:
|
|
return jsonify({"error": f"Unknown model: {model_id}"}), 404
|
|
|
|
headers = dict(request.headers)
|
|
headers.pop("Host", None)
|
|
|
|
try:
|
|
resp = requests.request(
|
|
method=request.method,
|
|
url=upstream_url,
|
|
headers=headers,
|
|
json=data,
|
|
stream=True,
|
|
timeout=None,
|
|
)
|
|
except Exception as e:
|
|
log.error(f"[Router] Erreur upstream: {e}")
|
|
return jsonify({"error": str(e)}), 502
|
|
|
|
excluded = {"content-encoding", "content-length", "transfer-encoding", "connection"}
|
|
response_headers = [
|
|
(name, value) for name, value in resp.headers.items()
|
|
if name.lower() not in excluded
|
|
]
|
|
|
|
return Response(
|
|
resp.raw,
|
|
status=resp.status_code,
|
|
headers=response_headers,
|
|
direct_passthrough=True,
|
|
)
|
|
|
|
|
|
@app.route("/", defaults={"path": ""}, methods=["GET", "POST", "PUT", "DELETE", "PATCH", "OPTIONS"])
|
|
@app.route("/<path:path>", methods=["GET", "POST", "PUT", "DELETE", "PATCH", "OPTIONS"])
|
|
def proxy(path):
|
|
"""Proxy générique pour les autres endpoints"""
|
|
if path.startswith("v1/chat/completions"):
|
|
return chat_completions()
|
|
|
|
upstream_url = f"http://{JEAN_PROXY_HOST}:{JEAN_PROXY_PORT}/{path}"
|
|
headers = dict(request.headers)
|
|
headers.pop("Host", None)
|
|
|
|
try:
|
|
resp = requests.request(
|
|
method=request.method,
|
|
url=upstream_url,
|
|
headers=headers,
|
|
data=request.get_data(),
|
|
cookies=request.cookies,
|
|
params=request.args,
|
|
allow_redirects=False,
|
|
stream=True,
|
|
timeout=None,
|
|
)
|
|
except Exception as e:
|
|
return Response(str(e), status=502)
|
|
|
|
excluded = {"content-encoding", "content-length", "transfer-encoding", "connection"}
|
|
response_headers = [
|
|
(name, value) for name, value in resp.headers.items()
|
|
if name.lower() not in excluded
|
|
]
|
|
|
|
return Response(
|
|
resp.raw,
|
|
status=resp.status_code,
|
|
headers=response_headers,
|
|
direct_passthrough=True,
|
|
)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
log.info(f"[Router] Démarrage sur port {LISTEN_PORT}")
|
|
log.info(f"[Router] Jean Web: {JEAN_WEB_HOST}:{JEAN_WEB_PORT}")
|
|
log.info(f"[Router] Jean Proxy: {JEAN_PROXY_HOST}:{JEAN_PROXY_PORT}")
|
|
if ENABLE_OLLAMA:
|
|
log.info(f"[Router] Ollama Proxy: {OLLAMA_PROXY_HOST}:{OLLAMA_PROXY_PORT}")
|
|
else:
|
|
log.info(f"[Router] Ollama: désactivé")
|
|
app.run(host="0.0.0.0", port=LISTEN_PORT, threaded=True)
|