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 - Automated maintenance cron job - LiteLLM config update
This commit is contained in:
Abiba
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.git
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__pycache__/
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*.pyc
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FROM python:3.12-slim
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WORKDIR /app
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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COPY dashboard.py .
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EXPOSE 3000
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CMD ["python", "dashboard.py"]
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"""SyslogAI Harness Dashboard — Modern Design."""
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import os, json, time, queue, threading
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import requests
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from flask import Flask, request, render_template_string, Response, stream_with_context
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ROUTER_METRICS = os.environ.get("ROUTER_METRICS_URL", "http://router:9000/metrics")
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app = Flask(__name__)
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sse_subscribers = []; sse_lock = threading.Lock()
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def fetch_state():
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try:
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r = requests.get(ROUTER_METRICS, timeout=5)
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if r.status_code == 200: return r.json()
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except Exception: pass
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return {"gpus":[],"route_counts":{},"agent_counts":{},"recent":[],"timestamp":time.time()}
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def broadcast_loop():
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while True:
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time.sleep(3)
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data = fetch_state(); payload = json.dumps(data)
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with sse_lock:
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dead = [q for q in sse_subscribers if not q.put(payload)]
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for q in dead: sse_subscribers.remove(q)
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threading.Thread(target=broadcast_loop, daemon=True).start()
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DASHBOARD_HTML = r"""<!DOCTYPE html>
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<html lang="en" data-bs-theme="dark">
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<head>
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<meta charset="UTF-8"><meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>SyslogAI Harness</title>
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<link href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.3/dist/css/bootstrap.min.css" rel="stylesheet">
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<style>
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body { background: #0b0f17; color: #bcc3cd; font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', system-ui, sans-serif; padding: 20px 24px; }
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.card { background: #111827; border: 1px solid #1e293b; border-radius: 10px; height: 100%; }
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.stat-card { background: #111827; border: 1px solid #1e293b; border-radius: 10px; padding: 18px 20px; text-align: center; }
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.stat-value { font-size: 28px; font-weight: 700; line-height: 1.1; }
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.stat-label { font-size: 11px; text-transform: uppercase; letter-spacing: 0.6px; color: #64748b; margin-top: 4px; }
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.gpu-card { background: #111827; border: 1px solid #1e293b; border-radius: 10px; padding: 16px 18px; height: 100%; }
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.gpu-card .title { font-size: 13px; font-weight: 600; color: #e2e8f0; margin-bottom: 12px; display: flex; align-items: center; gap: 8px; }
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.gpu-card .status-dot { width: 8px; height: 8px; border-radius: 50%; flex-shrink: 0; }
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.gpu-card .row-metric { display: flex; justify-content: space-between; font-size: 12px; padding: 2px 0; }
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.gpu-card .row-metric .lbl { color: #64748b; }
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.gpu-card .row-metric .val { color: #e2e8f0; font-variant-numeric: tabular-nums; }
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.gpu-card .slot-bar { display: flex; gap: 3px; margin-top: 8px; }
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.gpu-card .slot-bar .s { flex: 1; height: 5px; border-radius: 2px; background: #1e293b; }
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.gpu-card .slot-bar .s.active { background: #38bdf8; }
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.chart-card { background: #111827; border: 1px solid #1e293b; border-radius: 10px; padding: 16px 18px; height: 100%; display: flex; flex-direction: column; }
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.chart-card .title { font-size: 13px; font-weight: 600; color: #e2e8f0; margin-bottom: 12px; }
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.bar-row { margin-bottom: 8px; }
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.bar-label { display: flex; justify-content: space-between; font-size: 11px; margin-bottom: 3px; color: #64748b; }
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.bar-label .name { color: #cbd5e1; }
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.bar-track { height: 5px; background: #1e293b; border-radius: 3px; overflow: hidden; }
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.bar-fill { height: 100%; border-radius: 3px; transition: width 0.6s ease; }
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.table-custom { font-size: 11px; margin: 0; }
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.table-custom th { color: #64748b; font-weight: 500; font-size: 10px; text-transform: uppercase; border-color: #1e293b; padding: 8px 10px; }
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.table-custom td { color: #94a3b8; border-color: rgba(30,41,59,0.5); padding: 6px 10px; }
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.agent-badge { font-size: 10px; padding: 2px 7px; border-radius: 8px; font-weight: 600; }
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.btn-sm-period { font-size: 10px; padding: 3px 10px; border-radius: 6px; border: 1px solid #1e293b; color: #64748b; background: transparent; cursor: pointer; }
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.btn-sm-period.active { background: #1d4ed8; color: #fff; border-color: #1d4ed8; }
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.ring-label { font-size: 22px; font-weight: 700; }
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.ring-sublabel { font-size: 10px; color: #64748b; }
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</style>
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</head>
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<body>
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<!-- HEADER -->
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<div class="d-flex justify-content-between align-items-center mb-4">
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<div>
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<h5 class="mb-0 text-white fw-bold">⚡ SyslogAI Harness</h5>
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<div class="small text-secondary" id="live-indicator">
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<span class="status-dot" id="live-dot" style="width:6px;height:6px;border-radius:50%;display:inline-block;background:#22c55e;animation:pulse 2s infinite"></span>
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<span id="connection-status">live</span> · <span id="update-time"></span>
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</div>
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</div>
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<div class="d-flex gap-2">
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<div class="stat-card" style="min-width:100px"><div class="stat-value text-info" id="kpi-total">0</div><div class="stat-label">Requests</div></div>
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<div class="stat-card" style="min-width:100px"><div class="stat-value text-warning" id="kpi-active">0</div><div class="stat-label">Active</div></div>
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<div class="stat-card" style="min-width:100px"><div class="stat-value" style="color:#a78bfa" id="kpi-agents">0</div><div class="stat-label">Agents</div></div>
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</div>
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</div>
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<div class="row g-3 align-items-stretch">
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<!-- ROW 1: Usage Chart (8) + GPU Metrics (4) -->
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<div class="col-md-8"><div class="chart-card"><div class="title d-flex justify-content-between align-items-center">
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<span>Usage Over Time</span>
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<div class="d-flex gap-1">
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<button class="btn-sm-period active" onclick="switchPeriod('day')">24h</button>
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<button class="btn-sm-period" onclick="switchPeriod('week')">7d</button>
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<button class="btn-sm-period" onclick="switchPeriod('month')">30d</button>
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</div>
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</div><div id="timeseries-chart" style="height:150px"></div><div id="timeseries-legend" class="d-flex justify-content-center gap-3 mt-2 flex-wrap small"></div></div></div>
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<div class="col-md-4"><div class="chart-card"><div class="title">GPU Metrics</div><div id="gpu-metrics-card"></div></div></div>
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<!-- ROW 2: 3 GPU Cards -->
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<div class="col-md-4"><div class="gpu-card" id="gpu-moe"><div class="text-secondary small">Loading...</div></div></div>
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<div class="col-md-4"><div class="gpu-card" id="gpu-dense"><div class="text-secondary small">Loading...</div></div></div>
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<div class="col-md-4"><div class="gpu-card" id="gpu-light"><div class="text-secondary small">Loading...</div></div></div>
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<!-- ROW 3: Queue + Model + Agent -->
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<div class="col-md-4"><div class="chart-card"><div class="title">Queue Status</div><div class="text-center" id="queue-viz"></div></div></div>
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<div class="col-md-4"><div class="chart-card"><div class="title">Model Distribution</div><div id="route-bars"></div></div></div>
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<div class="col-md-4"><div class="chart-card"><div class="title">Agent Activity</div><div id="agent-bars"></div></div></div>
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<!-- ROW 4: Live Stream -->
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<div class="col-12"><div class="chart-card"><div class="title">Live Stream</div>
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<div class="table-responsive"><table class="table table-custom mb-0">
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<thead><tr><th>Time</th><th>Agent</th><th>Model</th><th>Reason</th><th>Tier</th></tr></thead>
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<tbody id="route-tbody"></tbody>
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</table></div>
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</div></div>
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</div>
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<script>
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var MC={'qwen3.5-9b-vlm':'#22c55e','qwen3.6-27B-code':'#f59e0b','qwen3.6-35B-A3B':'#a78bfa'};
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var ML={'qwen3.5-9b-vlm':'Qwen3.5 9B VLM','qwen3.6-27B-code':'Qwen Code','qwen3.6-35B-A3B':'Qwen MoE'};
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var GL={'qwen3.6-35B-A3B':'MoE - Strix Halo','qwen3.6-27B-code':'Dense - RTX 3090','qwen3.5-9b-vlm':'VLM - RTX 5070'};
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function $(id){return document.getElementById(id);}
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function render(data){
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if(!data||!data.gpus)return;
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var t=Object.values(data.route_counts||{}).reduce((a,b)=>a+b,0);
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var ta=0,tm=0;data.gpus.forEach(function(g){ta+=(g.active_requests||0);tm+=(g.max_concurrent||1)});
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$('kpi-total').textContent=t;$('kpi-active').textContent=ta+'/'+tm;$('kpi-agents').textContent=Object.keys(data.agent_counts||{}).length;
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$('update-time').textContent=new Date().toLocaleTimeString();
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var ids={'qwen3.6-35B-A3B':'gpu-moe','qwen3.6-27B-code':'gpu-dense','qwen3.5-9b-vlm':'gpu-light'};
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data.gpus.forEach(function(g){
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var el=$(ids[g.id]);if(!el)return;
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var a=g.active_requests||0,mx=g.max_concurrent||1;
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var sc=g.status==='healthy'?'#22c55e':g.status==='saturated'?'#f59e0b':'#ef4444';
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var ss=g.status==='healthy'?'Online':g.status==='saturated'?'Busy':'Offline';
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var slots='';for(var i=0;i<mx;i++)slots+='<span class=\"s'+(i<a?' active':'')+'\"></span>';
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var h='<div class=\"title\"><span class=\"status-dot\" style=\"background:'+sc+'\"></span>'+GL[g.id]+'<span class=\"ms-auto small\" style=\"color:'+sc+'\">'+ss+'</span></div>';
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h+='<div class=\"row-metric\"><span class=\"lbl\">VRAM</span><span class=\"val\">'+g.vram_used_mb+' / '+g.vram_total_mb+' MB</span></div>';
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h+='<div class=\"row-metric\"><span class=\"lbl\">Utilization</span><span class=\"val\">'+g.gpu_util_pct+'%</span></div>';
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h+='<div class=\"row-metric\"><span class=\"lbl\">Temperature</span><span class=\"val\" style=\"color:'+(g.temp_c>85?'#ef4444':g.temp_c>70?'#f59e0b':'#22c55e')+'\">'+g.temp_c+'C</span></div>';
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if(g.power_w)h+='<div class=\"row-metric\"><span class=\"lbl\">Power</span><span class=\"val\">'+g.power_w+'W'+(g.power_limit_w?'/'+g.power_limit_w+'W':'')+'</span></div>';
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h+='<div class=\"row-metric\"><span class=\"lbl\">Slots</span><span class=\"val\" style=\"color:'+(a>=mx?'#ef4444':'#e2e8f0')+'\">'+a+' / '+mx+'</span></div>';
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h+='<div class=\"slot-bar\">'+slots+'</div>';el.innerHTML=h;
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});
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renderQueue(data);renderGPUMetrics(data);
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var rc=data.route_counts||{},mr=Math.max(1,...Object.values(rc));
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$('route-bars').innerHTML=Object.entries(rc).length?Object.entries(rc).sort((a,b)=>b[1]-a[1]).map(function(e){var m=e[0],c=e[1];return'<div class=\"bar-row\"><div class=\"bar-label\"><span class=\"name\">'+(ML[m]||m)+'</span><span>'+c+' ('+(t?Math.round(c/t*100):0)+'%)</span></div><div class=\"bar-track\"><div class=\"bar-fill\" style=\"width:'+(c/mr*100)+'%;background:'+(MC[m]||'#38bdf8')+'\"></div></div></div>';}).join(''):'<div class=\"text-secondary small\">-</div>';
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var ac=data.agent_counts||{},ma=Math.max(1,...Object.values(ac));
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$('agent-bars').innerHTML=Object.entries(ac).length?Object.entries(ac).sort((a,b)=>b[1]-a[1]).map(function(e){return'<div class=\"bar-row\"><div class=\"bar-label\"><span class=\"name\">'+e[0]+'</span><span>'+e[1]+'</span></div><div class=\"bar-track\"><div class=\"bar-fill\" style=\"width:'+(e[1]/ma*100)+'%;background:#38bdf8\"></div></div></div>';}).join(''):'<div class=\"text-secondary small\">-</div>';
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var recent=data.recent||[];
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$('route-tbody').innerHTML=recent.length?recent.slice(0,20).map(function(r){var d=new Date(r.ts*1000),ag=r.agent||'?';return'<tr><td class=\"text-secondary\">'+d.toLocaleTimeString()+'</td><td><span class=\"agent-badge\" style=\"background:rgba(56,189,248,0.12);color:#38bdf8\">'+ag+'</span></td><td>'+(ML[r.model]||r.model)+'</td><td class=\"text-secondary\">'+(r.reason||'')+'</td><td class=\"text-uppercase\" style=\"font-size:10px;color:'+(r.tier==='enterprise'?'#a78bfa':'#64748b')+'\">'+(r.tier||'')+'</td></tr>';}).join(''):'<tr><td colspan=\"5\" class=\"text-secondary\">Waiting...</td></tr>';
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}
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function renderQueue(data){
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var el=$('queue-viz');if(!el)return;
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var ta=0,tm=0;data.gpus.forEach(function(g){ta+=(g.active_requests||0);tm+=(g.max_concurrent||1)});
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var pct=tm>0?Math.round(ta/tm*100):0,st=pct>=100?'SATURATED':pct>=50?'BUSY':'IDLE';
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var sc=pct>=100?'#ef4444':pct>=50?'#f59e0b':'#22c55e';
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var circ=188.5,dash=(pct/100)*circ;
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var h='<div class=\"d-inline-block position-relative mb-2\"><svg width=\"72\" height=\"72\"><circle cx=\"36\" cy=\"36\" r=\"30\" fill=\"none\" stroke=\"#1e293b\" stroke-width=\"6\"/><circle cx=\"36\" cy=\"36\" r=\"30\" fill=\"none\" stroke=\"'+sc+'\" stroke-width=\"6\" stroke-dasharray=\"'+dash+' '+(circ-dash)+'\" stroke-linecap=\"round\" transform=\"rotate(-90 36 36)\"/></svg><div style=\"position:absolute;top:50%;left:50%;transform:translate(-50%,-50%);text-align:center\"><div class=\"ring-label\" style=\"color:'+sc+'\">'+ta+'</div><div class=\"ring-sublabel\">/ '+tm+' slots</div></div></div>';
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h+='<div class=\"fw-bold mb-2 small\" style=\"color:'+sc+'\">'+st+'</div>';
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var lb={'qwen3.6-35B-A3B':'MoE','qwen3.6-27B-code':'Dense','qwen3.5-9b-vlm':'VLM'};
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data.gpus.forEach(function(g){var a=g.active_requests||0,mx=g.max_concurrent||1,gp=mx>0?Math.round(a/mx*100):0;h+='<div class=\"d-flex align-items-center gap-2 mb-1 justify-content-center\"><span class=\"small\" style=\"min-width:32px;text-align:right;font-size:10px\">'+(lb[g.id]||g.id)+'</span><div style=\"flex:1;max-width:70px;height:3px;background:#1e293b;border-radius:2px;overflow:hidden\"><div style=\"height:100%;width:'+gp+'%;background:'+sc+';border-radius:2px\"></div></div><span class=\"small\" style=\"min-width:22px;font-size:10px\">'+a+'/'+mx+'</span></div>'});
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el.innerHTML=h;
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}
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function renderGPUMetrics(data){
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var el=$('gpu-metrics-card');if(!el)return;
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var lb={'qwen3.6-35B-A3B':'MoE','qwen3.6-27B-code':'Dense','qwen3.5-9b-vlm':'VLM'};
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var h='';data.gpus.forEach(function(g){
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var nm=lb[g.id]||g.id,tp=g.temp_c||0,ut=g.gpu_util_pct||0,pw=g.power_w||0,pl=g.power_limit_w||0;
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var tc=tp>85?'#ef4444':tp>70?'#f59e0b':'#22c55e',uc=ut>90?'#ef4444':ut>70?'#f59e0b':'#22c55e';
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h+='<div class=\"mb-3\"><div class=\"fw-bold small text-white-50 mb-1\">'+nm+'</div>';
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h+='<div class=\"d-flex align-items-center gap-2 mb-1\"><span class=\"small text-secondary\" style=\"min-width:30px\">T</span><div class=\"flex-grow-1\" style=\"height:3px;background:#1e293b;border-radius:2px;overflow:hidden\"><div style=\"height:100%;width:'+Math.min(tp,100)+'%;background:'+tc+';border-radius:2px\"></div></div><span class=\"small\" style=\"color:'+tc+';min-width:30px;text-align:right\">'+tp+'C</span></div>';
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h+='<div class=\"d-flex align-items-center gap-2 mb-1\"><span class=\"small text-secondary\" style=\"min-width:30px\">U</span><div class=\"flex-grow-1\" style=\"height:3px;background:#1e293b;border-radius:2px;overflow:hidden\"><div style=\"height:100%;width:'+ut+'%;background:'+uc+';border-radius:2px\"></div></div><span class=\"small\" style=\"color:'+uc+';min-width:30px;text-align:right\">'+ut+'%</span></div>';
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if(pw>0){var pp=pl>0?Math.round(pw/pl*100):0,pc=pp>90?'#ef4444':pp>70?'#f59e0b':'#22c55e';h+='<div class=\"d-flex align-items-center gap-2\"><span class=\"small text-secondary\" style=\"min-width:30px\">P</span><div class=\"flex-grow-1\" style=\"height:3px;background:#1e293b;border-radius:2px;overflow:hidden\"><div style=\"height:100%;width:'+pp+'%;background:'+pc+';border-radius:2px\"></div></div><span class=\"small\" style=\"color:'+pc+';min-width:30px;text-align:right\">'+pw+'W</span></div>';}
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h+='</div>';});
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el.innerHTML=h;
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}
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var cp='day';
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function switchPeriod(p){cp=p;document.querySelectorAll('.btn-sm-period').forEach(function(b){b.classList.remove('active')});event.target.classList.add('active');loadTS();}
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function loadTS(){fetch('/api/timeseries?period='+cp).then(function(r){return r.json()}).then(renderTS).catch(function(){})}
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||||||
|
function renderTS(d){
|
||||||
|
var models=d.models||{},labels=d.labels||[];
|
||||||
|
if(!labels.length)return;
|
||||||
|
var cn=$('timeseries-chart'),lg=$('timeseries-legend'),mn=Object.keys(models);
|
||||||
|
if(!mn.length){cn.innerHTML='<div class=\"text-secondary small text-center py-4\">-</div>';return;}
|
||||||
|
var mv=1;for(var m in models)for(var i=0;i<models[m].length;i++)if(models[m][i]>mv)mv=models[m][i];mv=Math.ceil(mv*1.15)||1;
|
||||||
|
var W=labels.length>1?100/(labels.length-1):100,H=130;
|
||||||
|
var paths='';for(var mi=0;mi<mn.length;mi++){var m=mn[mi],vals=models[m]||[],d='';for(var i=0;i<vals.length;i++){var x=i*W,y=H-(vals[i]/mv)*H;d+=(i===0?'M':'L')+x.toFixed(1)+','+y.toFixed(1)+' ';}paths+='<path d=\"'+d+'\" fill=\"none\" stroke=\"'+(MC[m]||'#38bdf8')+'\" stroke-width=\"2\" stroke-linecap=\"round\" opacity=\"0.8\"/>';}
|
||||||
|
var grid='';for(var g=0;g<=4;g++){var y=(g/4)*H;grid+='<line x1=\"0\" y1=\"'+y.toFixed(1)+'\" x2=\"100\" y2=\"'+y.toFixed(1)+'\" stroke=\"#1e293b\" stroke-width=\"1\"/>';}
|
||||||
|
cn.innerHTML='<svg viewBox=\"0 0 100 '+(H+16)+'\" style=\"width:100%;height:'+(H+20)+'px;display:block\" preserveAspectRatio=\"none\">'+grid+paths+'</svg>';
|
||||||
|
lg.innerHTML=mn.map(function(m){return'<span class=\"d-flex align-items-center gap-1\"><svg width=\"14\" height=\"8\"><line x1=\"0\" y1=\"4\" x2=\"14\" y2=\"4\" stroke=\"'+(MC[m]||'#38bdf8')+'\" stroke-width=\"2\"/></svg>'+(ML[m]||m)+'</span>';}).join('');
|
||||||
|
}
|
||||||
|
function poll(){fetch('/api/state').then(function(r){return r.json()}).then(function(data){render(data);$('connection-status').textContent='live';}).catch(function(){$('connection-status').textContent='reconnecting';});}
|
||||||
|
poll();setInterval(poll,3000);loadTS();
|
||||||
|
</script>
|
||||||
|
</body>
|
||||||
|
</html>"""
|
||||||
|
|
||||||
|
@app.route("/")
|
||||||
|
def dashboard(): return render_template_string(DASHBOARD_HTML)
|
||||||
|
|
||||||
|
@app.route("/api/state")
|
||||||
|
def api_state(): return fetch_state()
|
||||||
|
|
||||||
|
@app.route("/api/timeseries")
|
||||||
|
def api_timeseries():
|
||||||
|
period = request.args.get("period", "day")
|
||||||
|
try:
|
||||||
|
r = requests.get("http://router:9000/metrics/timeseries?period=" + period, timeout=5)
|
||||||
|
if r.status_code == 200: return r.json()
|
||||||
|
except Exception: pass
|
||||||
|
return {"models": {}, "labels": []}
|
||||||
|
|
||||||
|
@app.route("/api/stream")
|
||||||
|
def api_stream():
|
||||||
|
def ev():
|
||||||
|
q = queue.Queue()
|
||||||
|
with sse_lock: sse_subscribers.append(q)
|
||||||
|
try:
|
||||||
|
yield "data: "+json.dumps(fetch_state())+"\n\n"
|
||||||
|
while True:
|
||||||
|
try: msg = q.get(timeout=3); yield "data: "+msg+"\n\n"
|
||||||
|
except queue.Empty: yield "data: "+json.dumps(fetch_state())+"\n\n"
|
||||||
|
except GeneratorExit: pass
|
||||||
|
finally:
|
||||||
|
with sse_lock:
|
||||||
|
if q in sse_subscribers: sse_subscribers.remove(q)
|
||||||
|
return Response(stream_with_context(ev()), mimetype="text/event-stream", headers={"Cache-Control":"no-cache","X-Accel-Buffering":"no","Access-Control-Allow-Origin":"*"})
|
||||||
|
|
||||||
|
@app.route("/health")
|
||||||
|
def health(): return {"status":"healthy","service":"harness-dashboard"}
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
app.run(host="0.0.0.0", port=3000, debug=False)
|
||||||
@@ -0,0 +1,2 @@
|
|||||||
|
flask==3.1.*
|
||||||
|
requests==2.32.*
|
||||||
@@ -0,0 +1,99 @@
|
|||||||
|
version: '3.8'
|
||||||
|
|
||||||
|
services:
|
||||||
|
redis:
|
||||||
|
image: redis:7-alpine
|
||||||
|
container_name: harness-redis
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "127.0.0.1:6379:6379"
|
||||||
|
volumes:
|
||||||
|
- redis-data:/data
|
||||||
|
command: redis-server --appendonly yes --maxmemory 256mb --maxmemory-policy allkeys-lru
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "redis-cli", "ping"]
|
||||||
|
interval: 10s
|
||||||
|
timeout: 3s
|
||||||
|
retries: 5
|
||||||
|
|
||||||
|
router:
|
||||||
|
build: ./router
|
||||||
|
container_name: harness-router
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "127.0.0.1:9000:9000"
|
||||||
|
environment:
|
||||||
|
- REDIS_URL=redis://redis:6379
|
||||||
|
- GPU_MOE_URL=http://192.168.68.15:8080/v1
|
||||||
|
- GPU_DENSE_URL=http://192.168.68.8:8080/v1
|
||||||
|
- GPU_LIGHT_URL=http://192.168.68.110:8080/v1
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:9000/health')"]
|
||||||
|
interval: 15s
|
||||||
|
timeout: 5s
|
||||||
|
retries: 3
|
||||||
|
depends_on:
|
||||||
|
redis:
|
||||||
|
condition: service_healthy
|
||||||
|
|
||||||
|
litellm:
|
||||||
|
image: ghcr.io/berriai/litellm:main-stable
|
||||||
|
command: ["--config", "/app/config.yaml", "--port", "4000"]
|
||||||
|
container_name: harness-litellm
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "127.0.0.1:8081:4000"
|
||||||
|
volumes:
|
||||||
|
- ./litellm_config.yaml:/app/config.yaml
|
||||||
|
environment:
|
||||||
|
- LITELLM_MASTER_KEY=sk-sys...-key
|
||||||
|
extra_hosts:
|
||||||
|
- "host.docker.internal:host-gateway"
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:4000/health/liveliness')"]
|
||||||
|
interval: 15s
|
||||||
|
timeout: 5s
|
||||||
|
retries: 3
|
||||||
|
depends_on:
|
||||||
|
redis:
|
||||||
|
condition: service_healthy
|
||||||
|
|
||||||
|
nginx:
|
||||||
|
image: nginx:alpine
|
||||||
|
container_name: harness-nginx
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "80:80"
|
||||||
|
volumes:
|
||||||
|
- ./nginx/nginx.conf:/etc/nginx/nginx.conf:ro
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "curl", "-f", "http://127.0.0.1/health"]
|
||||||
|
interval: 15s
|
||||||
|
timeout: 5s
|
||||||
|
retries: 3
|
||||||
|
depends_on:
|
||||||
|
- litellm
|
||||||
|
- dashboard
|
||||||
|
|
||||||
|
dashboard:
|
||||||
|
build: ./dashboard
|
||||||
|
container_name: harness-dashboard
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "127.0.0.1:3000:3000"
|
||||||
|
environment:
|
||||||
|
- REDIS_URL=redis://redis:6379
|
||||||
|
- GPU_SIDECARS=192.168.68.15:8090,192.168.68.8:8090,192.168.68.110:8090
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:3000/health')"]
|
||||||
|
interval: 15s
|
||||||
|
timeout: 5s
|
||||||
|
retries: 3
|
||||||
|
depends_on:
|
||||||
|
- redis
|
||||||
|
|
||||||
|
volumes:
|
||||||
|
redis-data:
|
||||||
|
|
||||||
|
# LiteLLM command override to load config
|
||||||
|
# (appended to fix config loading issue)
|
||||||
@@ -0,0 +1,97 @@
|
|||||||
|
version: '3.8'
|
||||||
|
|
||||||
|
services:
|
||||||
|
redis:
|
||||||
|
image: redis:7-alpine
|
||||||
|
container_name: harness-redis
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "127.0.0.1:6379:6379"
|
||||||
|
volumes:
|
||||||
|
- redis-data:/data
|
||||||
|
command: redis-server --appendonly yes --maxmemory 256mb --maxmemory-policy allkeys-lru
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "redis-cli", "ping"]
|
||||||
|
interval: 10s
|
||||||
|
timeout: 3s
|
||||||
|
retries: 5
|
||||||
|
|
||||||
|
router:
|
||||||
|
build: ./router
|
||||||
|
container_name: harness-router
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "9000:9000"
|
||||||
|
environment:
|
||||||
|
- REDIS_URL=redis://redis:6379
|
||||||
|
- GPU_MOE_URL=http://192.168.68.15:8080/v1
|
||||||
|
- GPU_DENSE_URL=http://192.168.68.8:8080/v1
|
||||||
|
- GPU_LIGHT_URL=http://192.168.68.110:8080/v1
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:9000/health')"]
|
||||||
|
interval: 15s
|
||||||
|
timeout: 5s
|
||||||
|
retries: 3
|
||||||
|
depends_on:
|
||||||
|
redis:
|
||||||
|
condition: service_healthy
|
||||||
|
|
||||||
|
litellm:
|
||||||
|
image: ghcr.io/berriai/litellm:main-stable
|
||||||
|
command: ["--config", "/app/config.yaml", "--port", "4000"]
|
||||||
|
container_name: harness-litellm
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "8081:4000"
|
||||||
|
volumes:
|
||||||
|
- ./litellm_config.yaml:/app/config.yaml
|
||||||
|
environment:
|
||||||
|
- LITELLM_MASTER_KEY=sk-syslog-local-master-key
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:4000/health/liveliness')"]
|
||||||
|
interval: 15s
|
||||||
|
timeout: 5s
|
||||||
|
retries: 3
|
||||||
|
depends_on:
|
||||||
|
redis:
|
||||||
|
condition: service_healthy
|
||||||
|
|
||||||
|
nginx:
|
||||||
|
image: nginx:alpine
|
||||||
|
container_name: harness-nginx
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "80:80"
|
||||||
|
volumes:
|
||||||
|
- ./nginx/nginx.conf:/etc/nginx/nginx.conf:ro
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "curl", "-f", "http://127.0.0.1/health"]
|
||||||
|
interval: 15s
|
||||||
|
timeout: 5s
|
||||||
|
retries: 3
|
||||||
|
depends_on:
|
||||||
|
- litellm
|
||||||
|
- dashboard
|
||||||
|
|
||||||
|
dashboard:
|
||||||
|
build: ./dashboard
|
||||||
|
container_name: harness-dashboard
|
||||||
|
restart: unless-stopped
|
||||||
|
ports:
|
||||||
|
- "3000:3000"
|
||||||
|
environment:
|
||||||
|
- REDIS_URL=redis://redis:6379
|
||||||
|
- GPU_SIDECARS=192.168.68.15:8090,192.168.68.8:8090,192.168.68.110:8090
|
||||||
|
healthcheck:
|
||||||
|
test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:3000/health')"]
|
||||||
|
interval: 15s
|
||||||
|
timeout: 5s
|
||||||
|
retries: 3
|
||||||
|
depends_on:
|
||||||
|
- redis
|
||||||
|
|
||||||
|
volumes:
|
||||||
|
redis-data:
|
||||||
|
|
||||||
|
# LiteLLM command override to load config
|
||||||
|
# (appended to fix config loading issue)
|
||||||
@@ -0,0 +1,25 @@
|
|||||||
|
model_list:
|
||||||
|
- model_name: qwen3.6-35B-A3B
|
||||||
|
litellm_params:
|
||||||
|
model: openai/qwen3.6-35B-A3B
|
||||||
|
api_base: http://192.168.68.15:8080/v1
|
||||||
|
api_key: "not-needed"
|
||||||
|
|
||||||
|
- model_name: qwen3.6-27B-code
|
||||||
|
litellm_params:
|
||||||
|
model: openai/qwen3.6-27B-code-text
|
||||||
|
api_base: http://192.168.68.8:8080/v1
|
||||||
|
api_key: "not-needed"
|
||||||
|
|
||||||
|
- model_name: qwen3.5-9b-vlm
|
||||||
|
litellm_params:
|
||||||
|
model: openai/qwen3.5-9b-vlm
|
||||||
|
api_base: http://192.168.68.110:8080/v1
|
||||||
|
api_key: "not-needed"
|
||||||
|
|
||||||
|
general_settings:
|
||||||
|
master_key: sk-syslog-local-master-key
|
||||||
|
|
||||||
|
litellm_settings:
|
||||||
|
drop_params: true
|
||||||
|
request_timeout: 120
|
||||||
Executable
+37
@@ -0,0 +1,37 @@
|
|||||||
|
#!/bin/bash
|
||||||
|
# SyslogAI Harness — Automated Maintenance
|
||||||
|
# Runs daily via cron
|
||||||
|
|
||||||
|
LOG="/var/log/harness-maintenance.log"
|
||||||
|
echo "=== $(date) ===" >> "$LOG"
|
||||||
|
|
||||||
|
# 1. Clean Redis timeseries keys older than 60 days
|
||||||
|
CUTOFF=$(date -d "60 days ago" +%Y%m%d%H)
|
||||||
|
echo "Redis: removing ts:* keys older than $CUTOFF" >> "$LOG"
|
||||||
|
DELETED=0
|
||||||
|
for key in $(docker exec harness-redis redis-cli KEYS "ts:*" 2>/dev/null); do
|
||||||
|
TS=$(echo "$key" | grep -oP '\d{10}$')
|
||||||
|
if [ -n "$TS" ] && [ "$TS" -lt "$CUTOFF" ] 2>/dev/null; then
|
||||||
|
docker exec harness-redis redis-cli DEL "$key" > /dev/null 2>&1
|
||||||
|
DELETED=$((DELETED + 1))
|
||||||
|
fi
|
||||||
|
done
|
||||||
|
echo "Redis: deleted $DELETED stale timeseries keys" >> "$LOG"
|
||||||
|
|
||||||
|
# 2. Log stale model keys (leftover from migrations)
|
||||||
|
STALE=$(docker exec harness-redis redis-cli KEYS "*gemma*" 2>/dev/null)
|
||||||
|
if [ -n "$STALE" ]; then
|
||||||
|
echo "WARNING: stale gemma keys found: $STALE" >> "$LOG"
|
||||||
|
fi
|
||||||
|
|
||||||
|
# 3. Prune Docker build cache (older than 7 days)
|
||||||
|
echo "Docker: pruning build cache" >> "$LOG"
|
||||||
|
docker builder prune -f --filter until=168h >> "$LOG" 2>&1
|
||||||
|
|
||||||
|
# 4. Log container health status
|
||||||
|
docker ps --format "table {{.Names}}\t{{.Status}}\t{{.RunningFor}}" >> "$LOG" 2>&1
|
||||||
|
|
||||||
|
# 5. Log Redis memory
|
||||||
|
docker exec harness-redis redis-cli INFO memory | grep used_memory_human >> "$LOG" 2>&1
|
||||||
|
|
||||||
|
echo "" >> "$LOG"
|
||||||
@@ -0,0 +1,88 @@
|
|||||||
|
worker_processes auto;
|
||||||
|
error_log /var/log/nginx/error.log warn;
|
||||||
|
pid /var/run/nginx.pid;
|
||||||
|
|
||||||
|
events { worker_connections 1024; }
|
||||||
|
|
||||||
|
http {
|
||||||
|
include /etc/nginx/mime.types;
|
||||||
|
default_type application/octet-stream;
|
||||||
|
|
||||||
|
log_format main '$remote_addr - $remote_user [$time_local] "$request" '
|
||||||
|
'$status $body_bytes_sent "$http_referer" '
|
||||||
|
'"$http_user_agent" rt=$request_time';
|
||||||
|
access_log /var/log/nginx/access.log main;
|
||||||
|
error_log /var/log/nginx/error.log;
|
||||||
|
sendfile on;
|
||||||
|
keepalive_timeout 65;
|
||||||
|
|
||||||
|
upstream router_api { server router:9000; }
|
||||||
|
upstream dashboard_ui { server dashboard:3000; }
|
||||||
|
upstream litellm_backend { server litellm:4000; }
|
||||||
|
|
||||||
|
server {
|
||||||
|
listen 80;
|
||||||
|
|
||||||
|
# Security headers
|
||||||
|
add_header X-Content-Type-Options nosniff always;
|
||||||
|
add_header X-Frame-Options SAMEORIGIN always;
|
||||||
|
add_header X-XSS-Protection "1; mode=block" always;
|
||||||
|
|
||||||
|
# Disable buffering for SSE streams
|
||||||
|
proxy_buffering off;
|
||||||
|
|
||||||
|
# API — through router
|
||||||
|
location /v1/ {
|
||||||
|
proxy_pass http://router_api;
|
||||||
|
proxy_http_version 1.1;
|
||||||
|
proxy_set_header Host $host;
|
||||||
|
proxy_set_header X-Real-IP $remote_addr;
|
||||||
|
proxy_set_header Authorization $http_authorization;
|
||||||
|
proxy_connect_timeout 10s;
|
||||||
|
proxy_read_timeout 600s;
|
||||||
|
proxy_buffering off;
|
||||||
|
}
|
||||||
|
|
||||||
|
# SSE streaming endpoint
|
||||||
|
location /stream {
|
||||||
|
proxy_pass http://router_api;
|
||||||
|
proxy_http_version 1.1;
|
||||||
|
proxy_set_header Host $host;
|
||||||
|
proxy_set_header Connection "";
|
||||||
|
proxy_buffering off;
|
||||||
|
chunked_transfer_encoding off;
|
||||||
|
}
|
||||||
|
|
||||||
|
# Dashboard API proxy for SSE
|
||||||
|
location /api/ {
|
||||||
|
proxy_pass http://dashboard_ui;
|
||||||
|
proxy_http_version 1.1;
|
||||||
|
proxy_set_header Host $host;
|
||||||
|
proxy_buffering off;
|
||||||
|
}
|
||||||
|
|
||||||
|
# LiteLLM debug
|
||||||
|
location /litellm/ {
|
||||||
|
rewrite ^/litellm/(.*) /$1 break;
|
||||||
|
proxy_pass http://litellm_backend;
|
||||||
|
proxy_http_version 1.1;
|
||||||
|
proxy_set_header Host $host;
|
||||||
|
proxy_set_header Authorization $http_authorization;
|
||||||
|
}
|
||||||
|
|
||||||
|
# Dashboard
|
||||||
|
location / {
|
||||||
|
proxy_pass http://dashboard_ui;
|
||||||
|
proxy_http_version 1.1;
|
||||||
|
proxy_set_header Host $host;
|
||||||
|
proxy_buffering off;
|
||||||
|
}
|
||||||
|
|
||||||
|
location /health {
|
||||||
|
proxy_pass http://router_api/health;
|
||||||
|
proxy_http_version 1.1;
|
||||||
|
proxy_set_header Host $host;
|
||||||
|
proxy_set_header X-Real-IP $remote_addr;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
@@ -0,0 +1,9 @@
|
|||||||
|
FROM python:3.12-slim
|
||||||
|
|
||||||
|
WORKDIR /app
|
||||||
|
COPY requirements.txt .
|
||||||
|
RUN pip install --no-cache-dir -r requirements.txt
|
||||||
|
COPY router.py .
|
||||||
|
|
||||||
|
EXPOSE 9000
|
||||||
|
CMD ["python", "router.py"]
|
||||||
@@ -0,0 +1,90 @@
|
|||||||
|
# Insert streaming support before the gpu_resp call
|
||||||
|
import re
|
||||||
|
with open('/opt/inference-harness/router/router.py') as f:
|
||||||
|
code = f.read()
|
||||||
|
|
||||||
|
# Find the gpu_resp block and replace with streaming-aware version
|
||||||
|
old = ''' start = time.time()
|
||||||
|
gpu_resp = requests.post(
|
||||||
|
gpu_url + "/chat/completions",
|
||||||
|
json=req_data,
|
||||||
|
headers={"Content-Type": "application/json", "Authorization": "Bearer not-needed"},
|
||||||
|
timeout=120,
|
||||||
|
)
|
||||||
|
latency_ms = int((time.time() - start) * 1000)
|
||||||
|
|
||||||
|
if gpu_resp.status_code != 200:
|
||||||
|
log.error("GPU error: %s %s", gpu_resp.status_code, gpu_resp.text[:200])
|
||||||
|
return jsonify({"error": "GPU backend returned " + str(gpu_resp.status_code)}), 502
|
||||||
|
|
||||||
|
response_data = gpu_resp.json()
|
||||||
|
response_data = fix_reasoning_content(response_data)
|
||||||
|
|
||||||
|
response_data["routing"] = {
|
||||||
|
"model": model, "reason": reason, "gpu": gpu_url,
|
||||||
|
"tier": tier, "agent": agent, "latency_ms": latency_ms,
|
||||||
|
}
|
||||||
|
|
||||||
|
return jsonify(response_data)'''
|
||||||
|
|
||||||
|
new = ''' start = time.time()
|
||||||
|
is_stream = req_data.get("stream", False)
|
||||||
|
|
||||||
|
gpu_resp = requests.post(
|
||||||
|
gpu_url + "/chat/completions",
|
||||||
|
json=req_data,
|
||||||
|
headers={"Content-Type": "application/json", "Authorization": "Bearer not-needed"},
|
||||||
|
timeout=120,
|
||||||
|
stream=is_stream,
|
||||||
|
)
|
||||||
|
latency_ms = int((time.time() - start) * 1000)
|
||||||
|
|
||||||
|
if gpu_resp.status_code != 200:
|
||||||
|
log.error("GPU error: %s %s", gpu_resp.status_code, gpu_resp.text[:200])
|
||||||
|
return jsonify({"error": "GPU backend returned " + str(gpu_resp.status_code)}), 502
|
||||||
|
|
||||||
|
if is_stream:
|
||||||
|
# Stream response back to client
|
||||||
|
def generate():
|
||||||
|
first = True
|
||||||
|
for line in gpu_resp.iter_lines(decode_unicode=True):
|
||||||
|
if line:
|
||||||
|
if first and line.startswith("data: "):
|
||||||
|
# Inject routing into first chunk
|
||||||
|
try:
|
||||||
|
chunk = json.loads(line[6:])
|
||||||
|
chunk["routing"] = {
|
||||||
|
"model": model, "reason": reason, "gpu": gpu_url,
|
||||||
|
"tier": tier, "agent": agent, "latency_ms": latency_ms,
|
||||||
|
}
|
||||||
|
yield "data: " + json.dumps(chunk) + "\n\n"
|
||||||
|
first = False
|
||||||
|
continue
|
||||||
|
except Exception:
|
||||||
|
pass
|
||||||
|
yield line + "\n"
|
||||||
|
yield "data: [DONE]\n\n"
|
||||||
|
return Response(stream_with_context(generate()), mimetype="text/event-stream")
|
||||||
|
|
||||||
|
response_data = gpu_resp.json()
|
||||||
|
response_data = fix_reasoning_content(response_data)
|
||||||
|
|
||||||
|
response_data["routing"] = {
|
||||||
|
"model": model, "reason": reason, "gpu": gpu_url,
|
||||||
|
"tier": tier, "agent": agent, "latency_ms": latency_ms,
|
||||||
|
}
|
||||||
|
|
||||||
|
return jsonify(response_data)'''
|
||||||
|
|
||||||
|
code = code.replace(old, new)
|
||||||
|
|
||||||
|
# Add missing import
|
||||||
|
if 'from flask import Flask, request, jsonify' in code:
|
||||||
|
code = code.replace(
|
||||||
|
'from flask import Flask, request, jsonify',
|
||||||
|
'from flask import Flask, request, jsonify, Response, stream_with_context'
|
||||||
|
)
|
||||||
|
|
||||||
|
with open('/opt/inference-harness/router/router.py', 'w') as f:
|
||||||
|
f.write(code)
|
||||||
|
print('Streaming support added')
|
||||||
@@ -0,0 +1,3 @@
|
|||||||
|
flask==3.1.*
|
||||||
|
redis==5.2.*
|
||||||
|
requests==2.32.*
|
||||||
@@ -0,0 +1,341 @@
|
|||||||
|
import os, json, time, logging, traceback, threading, queue
|
||||||
|
import requests, redis
|
||||||
|
from flask import Flask, request, jsonify, Response, stream_with_context
|
||||||
|
|
||||||
|
REDIS_URL = os.environ.get("REDIS_URL", "redis://redis:6379")
|
||||||
|
GPU_MOE_URL = os.environ.get("GPU_MOE_URL", "http://192.168.68.15:8080/v1")
|
||||||
|
GPU_DENSE_URL = os.environ.get("GPU_DENSE_URL", "http://192.168.68.8:8080/v1")
|
||||||
|
GPU_LIGHT_URL = os.environ.get("GPU_LIGHT_URL", "http://192.168.68.110:8080/v1")
|
||||||
|
|
||||||
|
GPU_SIDECARS = {
|
||||||
|
"qwen3.6-35B-A3B": "http://192.168.68.15:8090",
|
||||||
|
"qwen3.6-27B-code": "http://192.168.68.8:8090",
|
||||||
|
"qwen3.5-9b-vlm": "http://192.168.68.110:8090",
|
||||||
|
}
|
||||||
|
GPU_URLS = {
|
||||||
|
"qwen3.6-35B-A3B": GPU_MOE_URL,
|
||||||
|
"qwen3.6-27B-code": GPU_DENSE_URL,
|
||||||
|
"qwen3.5-9b-vlm": GPU_LIGHT_URL,
|
||||||
|
}
|
||||||
|
# Max concurrent requests per GPU (based on llama.cpp --parallel)
|
||||||
|
GPU_MAX_CONCURRENT = {
|
||||||
|
"qwen3.6-35B-A3B": 2, # 2 slots
|
||||||
|
"qwen3.6-27B-code": 2, # 2 slots
|
||||||
|
"qwen3.5-9b-vlm": 2, # 2 slots (12GB VRAM, 4GB headroom)
|
||||||
|
}
|
||||||
|
|
||||||
|
TIER_MODELS = {
|
||||||
|
"starter": ["qwen3.5-9b-vlm"],
|
||||||
|
"professional": ["qwen3.6-35B-A3B", "qwen3.6-27B-code", "qwen3.5-9b-vlm"],
|
||||||
|
"enterprise": ["qwen3.6-35B-A3B", "qwen3.6-27B-code", "qwen3.5-9b-vlm"],
|
||||||
|
}
|
||||||
|
API_KEYS = {
|
||||||
|
"sk-syslog-local-master-key": {"tier": "enterprise", "agent": "admin"},
|
||||||
|
"sk-syslog-abiba": {"tier": "enterprise", "agent": "Abiba"},
|
||||||
|
"sk-syslog-mumuni": {"tier": "enterprise", "agent": "Mumuni"},
|
||||||
|
"sk-syslog-tanko": {"tier": "enterprise", "agent": "Tanko"},
|
||||||
|
"sk-syslog-koby": {"tier": "enterprise", "agent": "Koby"},
|
||||||
|
"sk-syslog-kagenz0": {"tier": "enterprise", "agent": "Kagenz0"},
|
||||||
|
"sk-syslog-koonimo": {"tier": "enterprise", "agent": "Koonimo"},
|
||||||
|
"sk-starter-abc123": {"tier": "starter", "agent": "test-starter"},
|
||||||
|
"sk-professional-xyz789": {"tier": "professional", "agent": "test-pro"},
|
||||||
|
}
|
||||||
|
|
||||||
|
logging.basicConfig(level=logging.INFO, format="%(asctime)s [ROUTER] %(levelname)s %(message)s")
|
||||||
|
log = logging.getLogger("router")
|
||||||
|
try: r = redis.from_url(REDIS_URL, decode_responses=True); r.ping()
|
||||||
|
except Exception: r = None
|
||||||
|
|
||||||
|
|
||||||
|
def counter_audit_loop():
|
||||||
|
"""Every 30s, check GPU slots and reset counters if all slots idle."""
|
||||||
|
while True:
|
||||||
|
time.sleep(30)
|
||||||
|
if not r: continue
|
||||||
|
for model, url in GPU_URLS.items():
|
||||||
|
try:
|
||||||
|
resp = requests.get(url.replace("/v1","") + "/slots",
|
||||||
|
headers={"Authorization": "Bearer not-needed"}, timeout=5)
|
||||||
|
if resp.status_code == 200:
|
||||||
|
slots = resp.json()
|
||||||
|
all_idle = all(not s.get("is_processing", False) for s in slots)
|
||||||
|
if all_idle:
|
||||||
|
current = int(r.get("active:" + model) or 0)
|
||||||
|
if current > 0:
|
||||||
|
r.set("active:" + model, 0)
|
||||||
|
log.info("AUDIT: Reset stuck counter for %s (was %d)", model, current)
|
||||||
|
except Exception:
|
||||||
|
pass
|
||||||
|
|
||||||
|
threading.Thread(target=counter_audit_loop, daemon=True).start()
|
||||||
|
|
||||||
|
app = Flask(__name__)
|
||||||
|
sse_subscribers = []; sse_lock = threading.Lock()
|
||||||
|
|
||||||
|
def gpu_active_count(model):
|
||||||
|
"""Get number of in-flight requests for a GPU."""
|
||||||
|
if r:
|
||||||
|
return int(r.get("active:" + model) or 0)
|
||||||
|
return 0
|
||||||
|
|
||||||
|
def gpu_incr(model):
|
||||||
|
if r: r.incr("active:" + model)
|
||||||
|
|
||||||
|
def gpu_decr(model):
|
||||||
|
if r:
|
||||||
|
v = r.decr("active:" + model)
|
||||||
|
if v and int(v) < 0:
|
||||||
|
r.set("active:" + model, 0) # never go negative
|
||||||
|
|
||||||
|
def check_gpu_health(model):
|
||||||
|
url = GPU_SIDECARS.get(model)
|
||||||
|
if not url: return {"status": "unknown"}
|
||||||
|
try:
|
||||||
|
resp = requests.get(url, timeout=5)
|
||||||
|
if resp.status_code == 200:
|
||||||
|
d = resp.json()
|
||||||
|
pct = (d.get("vram_used_mb",0) / max(d.get("vram_total_mb",1), 1)) * 100
|
||||||
|
status = "healthy" if pct < 90 else "saturated"
|
||||||
|
# Also check if llama.cpp endpoint is actually responding
|
||||||
|
gpu_url = GPU_URLS.get(model, "")
|
||||||
|
try:
|
||||||
|
hr = requests.get(gpu_url.replace("/v1","") + "/health", headers={"Authorization": "Bearer not-needed"}, timeout=3)
|
||||||
|
if hr.status_code != 200:
|
||||||
|
status = "down"
|
||||||
|
except Exception:
|
||||||
|
status = "down"
|
||||||
|
return {"status": status, "vram_used_mb": d.get("vram_used_mb"), "vram_total_mb": d.get("vram_total_mb"), "vram_pct": round(pct,1), "temp_c": d.get("temp_c"), "gpu_util_pct": d.get("gpu_util_pct"), "gpu_name": d.get("gpu_name"), "power_w": d.get("power_w"), "power_limit_w": d.get("power_limit_w")}
|
||||||
|
except Exception: pass
|
||||||
|
return {"status": "down"}
|
||||||
|
|
||||||
|
def available_models(): return [m for m in GPU_URLS if check_gpu_health(m)["status"] in ("healthy","saturated")]
|
||||||
|
|
||||||
|
def estimate_tokens(msgs): return sum(len(str(m.get("content",""))) for m in msgs) // 4
|
||||||
|
|
||||||
|
def is_gpu_busy(model):
|
||||||
|
"""Check if GPU is at or near max concurrent capacity."""
|
||||||
|
active = gpu_active_count(model)
|
||||||
|
max_c = GPU_MAX_CONCURRENT.get(model, 1)
|
||||||
|
return active >= max_c
|
||||||
|
|
||||||
|
def select_best_gpu(candidates, reason):
|
||||||
|
"""Pick the best GPU from candidates, preferring least-loaded."""
|
||||||
|
best = None
|
||||||
|
best_load = 999
|
||||||
|
for m in candidates:
|
||||||
|
load = gpu_active_count(m)
|
||||||
|
if load < best_load:
|
||||||
|
best_load = load
|
||||||
|
best = m
|
||||||
|
if best:
|
||||||
|
actual_reason = reason
|
||||||
|
if is_gpu_busy(best):
|
||||||
|
actual_reason = "load_balanced_" + reason
|
||||||
|
return {"model": best, "reason": actual_reason}
|
||||||
|
return None
|
||||||
|
|
||||||
|
def route(rd, tier):
|
||||||
|
msgs = rd.get("messages",[]); t = estimate_tokens(msgs)
|
||||||
|
sys = any(m.get("role")=="system" for m in msgs)
|
||||||
|
turns = len([m for m in msgs if m.get("role") in ("user","assistant")])
|
||||||
|
hints = rd.get("routing_hints",{})
|
||||||
|
allowed = TIER_MODELS.get(tier, ["qwen3.5-9b-vlm"])
|
||||||
|
avail = [m for m in available_models() if m in allowed]
|
||||||
|
if not avail: return {"model": allowed[0], "reason": "all_saturated", "saturated": True}
|
||||||
|
|
||||||
|
req = rd.get("model","auto")
|
||||||
|
if req != "auto":
|
||||||
|
target = req if req in avail else avail[0]
|
||||||
|
# If explicit model is busy, check if another can take it
|
||||||
|
if is_gpu_busy(target) and req in allowed:
|
||||||
|
alts = [m for m in avail if m != target and m in allowed]
|
||||||
|
if alts:
|
||||||
|
alt = select_best_gpu(alts, "explicit")
|
||||||
|
if alt: return alt
|
||||||
|
return {"model": target, "reason": "explicit"}
|
||||||
|
|
||||||
|
if hints:
|
||||||
|
if hints.get("priority")=="speed" and "qwen3.5-9b-vlm" in avail:
|
||||||
|
return select_best_gpu(["qwen3.5-9b-vlm"], "hint_speed") or {"model":"qwen3.5-9b-vlm","reason":"hint_speed"}
|
||||||
|
if hints.get("priority")=="quality" and "qwen3.6-27B-code" in avail:
|
||||||
|
return select_best_gpu(["qwen3.6-27B-code"], "hint_quality") or {"model":"qwen3.6-27B-code","reason":"hint_quality"}
|
||||||
|
|
||||||
|
# Heavy -> dense (but fall back to MoE if dense is busy)
|
||||||
|
if t > 4000 or sys or turns > 6:
|
||||||
|
candidates = ["qwen3.6-27B-code","qwen3.6-35B-A3B","qwen3.5-9b-vlm"]
|
||||||
|
candidates = [m for m in candidates if m in avail]
|
||||||
|
result = select_best_gpu(candidates, "heavy_reasoning")
|
||||||
|
if result: return result
|
||||||
|
|
||||||
|
# Ultra-light -> VLM
|
||||||
|
first_msg = msgs[0].get("content","") if msgs else ""
|
||||||
|
words = len(first_msg.split()) if isinstance(first_msg, str) else 99
|
||||||
|
if words <= 3 and turns <= 1 and not sys and "qwen3.5-9b-vlm" in avail:
|
||||||
|
if not is_gpu_busy("qwen3.5-9b-vlm"):
|
||||||
|
return {"model":"qwen3.5-9b-vlm","reason":"ultra_light"}
|
||||||
|
|
||||||
|
# Default: MoE, fall back to dense if MoE is busy
|
||||||
|
if "qwen3.6-35B-A3B" in avail:
|
||||||
|
if is_gpu_busy("qwen3.6-35B-A3B") and "qwen3.6-27B-code" in avail:
|
||||||
|
return {"model": "qwen3.6-27B-code", "reason": "load_balanced_default"}
|
||||||
|
return {"model":"qwen3.6-35B-A3B","reason":"default_moe"}
|
||||||
|
|
||||||
|
return {"model":avail[0],"reason":"fallback"}
|
||||||
|
|
||||||
|
def clean_unicode(text):
|
||||||
|
if not isinstance(text, str): return text
|
||||||
|
text = text.replace(chr(0x2014), "-"); text = text.replace(chr(0x2013), "-")
|
||||||
|
text = text.replace(chr(0x2018), "'"); text = text.replace(chr(0x2019), "'")
|
||||||
|
text = text.replace(chr(0x201C), '"'); text = text.replace(chr(0x201D), '"')
|
||||||
|
text = text.replace(chr(0x2026), "..."); text = text.replace(chr(0x00A0), " ")
|
||||||
|
return text.encode("ascii", "ignore").decode("ascii")
|
||||||
|
|
||||||
|
def clean_response(d):
|
||||||
|
if isinstance(d, dict): return {k: clean_response(v) for k,v in d.items()}
|
||||||
|
if isinstance(d, list): return [clean_response(v) for v in d]
|
||||||
|
if isinstance(d, str): return clean_unicode(d)
|
||||||
|
return d
|
||||||
|
|
||||||
|
def get_metrics():
|
||||||
|
d = {"gpus":[],"route_counts":{},"agent_counts":{},"tier_counts":{},"recent":[],"timestamp":time.time(),"active_requests":{}}
|
||||||
|
for m in GPU_URLS:
|
||||||
|
h = check_gpu_health(m)
|
||||||
|
d["gpus"].append({"id":m,"gpu_name":h.get("gpu_name",m),"status":h.get("status"),"vram_used_mb":h.get("vram_used_mb"),"vram_total_mb":h.get("vram_total_mb"),"vram_pct":h.get("vram_pct"),"temp_c":h.get("temp_c"),"gpu_util_pct":h.get("gpu_util_pct"),"power_w":h.get("power_w"),"power_limit_w":h.get("power_limit_w"),"active_requests":gpu_active_count(m), "max_concurrent": GPU_MAX_CONCURRENT.get(m, 1)})
|
||||||
|
d["active_requests"][m] = gpu_active_count(m)
|
||||||
|
if r:
|
||||||
|
try:
|
||||||
|
for m in GPU_URLS: d["route_counts"][m] = int(r.get("routes:"+m) or 0)
|
||||||
|
for k,v in API_KEYS.items():
|
||||||
|
c = int(r.get("routes:agent:"+v["agent"]) or 0)
|
||||||
|
if c>0: d["agent_counts"][v["agent"]] = c
|
||||||
|
for t in TIER_MODELS: d["tier_counts"][t] = int(r.get("routes:tier:"+t) or 0)
|
||||||
|
raw = r.lrange("routes:recent",0,49)
|
||||||
|
d["recent"] = [json.loads(x) for x in raw] if raw else []
|
||||||
|
except Exception: pass
|
||||||
|
return d
|
||||||
|
|
||||||
|
def bcast():
|
||||||
|
data = get_metrics(); payload = json.dumps(data)
|
||||||
|
with sse_lock:
|
||||||
|
dead = []
|
||||||
|
for q in sse_subscribers:
|
||||||
|
try: q.put(payload)
|
||||||
|
except Exception: dead.append(q)
|
||||||
|
for q in dead: sse_subscribers.remove(q)
|
||||||
|
|
||||||
|
@app.route("/v1/chat/completions", methods=["POST"])
|
||||||
|
def chat():
|
||||||
|
try:
|
||||||
|
rd = request.get_json(force=True)
|
||||||
|
ak = request.headers.get("Authorization","").replace("Bearer ","")
|
||||||
|
ki = API_KEYS.get(ak, {"tier":"starter","agent":"unknown"})
|
||||||
|
tier, agent = ki["tier"], ki["agent"]
|
||||||
|
d = route(rd, tier)
|
||||||
|
if d.get("saturated"):
|
||||||
|
resp = jsonify({"error": "All GPUs saturated", "retry_after_s": 5})
|
||||||
|
resp.headers["Retry-After"] = "5"
|
||||||
|
return resp, 503
|
||||||
|
model, reason, url = d["model"], d["reason"], GPU_URLS[d["model"]]
|
||||||
|
is_stream = rd.get("stream", False)
|
||||||
|
|
||||||
|
gpu_incr(model)
|
||||||
|
|
||||||
|
log.info("ROUTE: %s -> %s (%s) stream=%s active=%d/%d", agent, model, reason, is_stream, gpu_active_count(model), GPU_MAX_CONCURRENT.get(model,1))
|
||||||
|
if r:
|
||||||
|
try:
|
||||||
|
r.incr("routes:"+model); r.incr("routes:tier:"+tier); r.incr("routes:agent:"+agent)
|
||||||
|
r.incr("ts:"+model+":"+time.strftime("%Y%m%d%H"))
|
||||||
|
r.lpush("routes:recent", json.dumps({"ts":time.time(),"model":model,"reason":reason,"tier":tier,"agent":agent}))
|
||||||
|
r.ltrim("routes:recent",0,999)
|
||||||
|
except Exception: pass
|
||||||
|
start = time.time()
|
||||||
|
resp = requests.post(url+"/chat/completions", json=rd,
|
||||||
|
headers={"Content-Type":"application/json","Authorization":"Bearer not-needed"}, timeout=300, stream=is_stream)
|
||||||
|
lat = int((time.time()-start)*1000)
|
||||||
|
gpu_decr(model)
|
||||||
|
|
||||||
|
if resp.status_code != 200: return jsonify({"error":"GPU error "+str(resp.status_code)}), 502
|
||||||
|
if is_stream:
|
||||||
|
def gen():
|
||||||
|
for raw in resp.iter_content(chunk_size=None, decode_unicode=True):
|
||||||
|
if raw: yield clean_unicode(raw)
|
||||||
|
bcast()
|
||||||
|
return Response(stream_with_context(gen()), mimetype="text/event-stream")
|
||||||
|
data = clean_response(resp.json())
|
||||||
|
for c in data.get("choices",[]):
|
||||||
|
msg = c.get("message",{})
|
||||||
|
if not msg.get("content") and msg.get("reasoning_content"):
|
||||||
|
msg["content"] = msg["reasoning_content"]
|
||||||
|
data["routing"] = {"model":model,"reason":reason,"gpu":url,"tier":tier,"agent":agent,"latency_ms":lat,"active_gpu":gpu_active_count(model)}
|
||||||
|
bcast()
|
||||||
|
return jsonify(data)
|
||||||
|
except requests.Timeout:
|
||||||
|
gpu_decr(model)
|
||||||
|
log.error("TIMEOUT: %s -> %s", agent, model)
|
||||||
|
return jsonify({"error":"timeout"}), 504
|
||||||
|
except Exception as e:
|
||||||
|
gpu_decr(model)
|
||||||
|
log.error("Error: %s\n%s", e, traceback.format_exc())
|
||||||
|
return jsonify({"error":str(e)}), 500
|
||||||
|
|
||||||
|
@app.route("/v1/models")
|
||||||
|
def models(): return jsonify({"object":"list","data":[{"id":m,"object":"model","owned_by":"syslog","status":check_gpu_health(m).get("status"),"gpu":check_gpu_health(m).get("gpu_name")} for m in GPU_URLS]})
|
||||||
|
|
||||||
|
@app.route("/health")
|
||||||
|
def health():
|
||||||
|
gpus = {}
|
||||||
|
for m in GPU_URLS:
|
||||||
|
h = check_gpu_health(m)
|
||||||
|
h["active_requests"] = gpu_active_count(m)
|
||||||
|
h["max_concurrent"] = GPU_MAX_CONCURRENT.get(m, 1)
|
||||||
|
gpus[m] = h
|
||||||
|
return jsonify({"status":"healthy","redis":"connected" if r else "down","gpus":gpus,"available_models":available_models()})
|
||||||
|
|
||||||
|
@app.route("/metrics")
|
||||||
|
def metrics(): return jsonify(get_metrics())
|
||||||
|
|
||||||
|
@app.route("/metrics/timeseries")
|
||||||
|
def metrics_timeseries():
|
||||||
|
period = request.args.get("period", "day"); models_list = list(GPU_URLS.keys())
|
||||||
|
data = {"models": {}, "labels": []}
|
||||||
|
if period == "day":
|
||||||
|
buckets = [time.strftime("%Y%m%d%H", time.gmtime(time.time()-h*3600)) for h in range(23,-1,-1)]
|
||||||
|
data["labels"] = [time.strftime("%H:00", time.gmtime(time.time()-h*3600)) for h in range(23,-1,-1)]
|
||||||
|
elif period == "week":
|
||||||
|
buckets = [time.strftime("%Y%m%d", time.gmtime(time.time()-d*86400)) for d in range(6,-1,-1)]
|
||||||
|
data["labels"] = [time.strftime("%a", time.gmtime(time.time()-d*86400)) for d in range(6,-1,-1)]
|
||||||
|
else:
|
||||||
|
buckets = [time.strftime("%Y%m%d", time.gmtime(time.time()-d*86400)) for d in range(29,-1,-1)]
|
||||||
|
data["labels"] = [time.strftime("%m/%d", time.gmtime(time.time()-d*86400)) for d in range(29,-1,-1)]
|
||||||
|
if r:
|
||||||
|
for model in models_list:
|
||||||
|
counts = []
|
||||||
|
for bucket in buckets:
|
||||||
|
total = 0
|
||||||
|
if period in ("week","month"):
|
||||||
|
for hh in range(24): total += int(r.get("ts:"+model+":"+bucket+"{:02d}".format(hh)) or 0)
|
||||||
|
else: total = int(r.get("ts:"+model+":"+bucket) or 0)
|
||||||
|
counts.append(total)
|
||||||
|
data["models"][model] = counts
|
||||||
|
return jsonify(data)
|
||||||
|
|
||||||
|
@app.route("/stream")
|
||||||
|
def stream():
|
||||||
|
def ev():
|
||||||
|
q = queue.Queue()
|
||||||
|
with sse_lock: sse_subscribers.append(q)
|
||||||
|
try:
|
||||||
|
yield "data: "+json.dumps(get_metrics())+"\n\n"
|
||||||
|
while True:
|
||||||
|
try: yield "data: "+q.get(timeout=3)+"\n\n"
|
||||||
|
except queue.Empty: yield "data: "+json.dumps(get_metrics())+"\n\n"
|
||||||
|
except GeneratorExit: pass
|
||||||
|
finally:
|
||||||
|
with sse_lock:
|
||||||
|
if q in sse_subscribers: sse_subscribers.remove(q)
|
||||||
|
return Response(stream_with_context(ev()), mimetype="text/event-stream",
|
||||||
|
headers={"Cache-Control":"no-cache","X-Accel-Buffering":"no","Access-Control-Allow-Origin":"*"})
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
log.info("Router on :9000 (load-aware)")
|
||||||
|
app.run(host="0.0.0.0", port=9000, debug=False)
|
||||||
@@ -0,0 +1,342 @@
|
|||||||
|
import os, json, time, logging, traceback, threading, queue
|
||||||
|
import requests, redis
|
||||||
|
from flask import Flask, request, jsonify, Response, stream_with_context
|
||||||
|
|
||||||
|
REDIS_URL = os.environ.get("REDIS_URL", "redis://redis:6379")
|
||||||
|
GPU_MOE_URL = os.environ.get("GPU_MOE_URL", "http://192.168.68.15:8080/v1")
|
||||||
|
GPU_DENSE_URL = os.environ.get("GPU_DENSE_URL", "http://192.168.68.8:8080/v1")
|
||||||
|
GPU_LIGHT_URL = os.environ.get("GPU_LIGHT_URL", "http://192.168.68.110:8080/v1")
|
||||||
|
|
||||||
|
GPU_SIDECARS = {
|
||||||
|
"qwen3.6-35B-A3B": "http://192.168.68.15:8090",
|
||||||
|
"qwen3.6-27B-code": "http://192.168.68.8:8090",
|
||||||
|
"qwen3.5-9b-vlm": "http://192.168.68.110:8090",
|
||||||
|
}
|
||||||
|
GPU_URLS = {
|
||||||
|
"qwen3.6-35B-A3B": GPU_MOE_URL,
|
||||||
|
"qwen3.6-27B-code": GPU_DENSE_URL,
|
||||||
|
"qwen3.5-9b-vlm": GPU_LIGHT_URL,
|
||||||
|
}
|
||||||
|
# Max concurrent requests per GPU (based on llama.cpp --parallel)
|
||||||
|
GPU_MAX_CONCURRENT = {
|
||||||
|
"qwen3.6-35B-A3B": 2, # 2 slots
|
||||||
|
"qwen3.6-27B-code": 2, # 2 slots
|
||||||
|
"qwen3.5-9b-vlm": 1, # 1 slot
|
||||||
|
}
|
||||||
|
|
||||||
|
TIER_MODELS = {
|
||||||
|
"starter": ["qwen3.5-9b-vlm"],
|
||||||
|
"professional": ["qwen3.6-35B-A3B", "qwen3.6-27B-code", "qwen3.5-9b-vlm"],
|
||||||
|
"enterprise": ["qwen3.6-35B-A3B", "qwen3.6-27B-code", "qwen3.5-9b-vlm"],
|
||||||
|
}
|
||||||
|
API_KEYS = {
|
||||||
|
"sk-syslog-local-master-key": {"tier": "enterprise", "agent": "admin"},
|
||||||
|
"sk-syslog-abiba": {"tier": "enterprise", "agent": "Abiba"},
|
||||||
|
"sk-syslog-mumuni": {"tier": "enterprise", "agent": "Mumuni"},
|
||||||
|
"sk-syslog-tanko": {"tier": "enterprise", "agent": "Tanko"},
|
||||||
|
"sk-syslog-koby": {"tier": "enterprise", "agent": "Koby"},
|
||||||
|
"sk-syslog-kagenz0": {"tier": "enterprise", "agent": "Kagenz0"},
|
||||||
|
"sk-syslog-koonimo": {"tier": "enterprise", "agent": "Koonimo"},
|
||||||
|
"sk-starter-abc123": {"tier": "starter", "agent": "test-starter"},
|
||||||
|
"sk-professional-xyz789": {"tier": "professional", "agent": "test-pro"},
|
||||||
|
}
|
||||||
|
|
||||||
|
logging.basicConfig(level=logging.INFO, format="%(asctime)s [ROUTER] %(levelname)s %(message)s")
|
||||||
|
log = logging.getLogger("router")
|
||||||
|
try: r = redis.from_url(REDIS_URL, decode_responses=True); r.ping()
|
||||||
|
except Exception: r = None
|
||||||
|
|
||||||
|
|
||||||
|
def counter_audit_loop():
|
||||||
|
"""Every 30s, check GPU slots and reset counters if all slots idle."""
|
||||||
|
while True:
|
||||||
|
time.sleep(30)
|
||||||
|
if not r: continue
|
||||||
|
for model, url in GPU_URLS.items():
|
||||||
|
try:
|
||||||
|
resp = requests.get(url.replace("/v1","") + "/slots",
|
||||||
|
headers={"Authorization": "Bearer not-needed"}, timeout=5)
|
||||||
|
if resp.status_code == 200:
|
||||||
|
slots = resp.json()
|
||||||
|
all_idle = all(not s.get("is_processing", False) for s in slots)
|
||||||
|
if all_idle:
|
||||||
|
current = int(r.get("active:" + model) or 0)
|
||||||
|
if current > 0:
|
||||||
|
r.set("active:" + model, 0)
|
||||||
|
log.info("AUDIT: Reset stuck counter for %s (was %d)", model, current)
|
||||||
|
except Exception:
|
||||||
|
pass
|
||||||
|
|
||||||
|
threading.Thread(target=counter_audit_loop, daemon=True).start()
|
||||||
|
|
||||||
|
app = Flask(__name__)
|
||||||
|
sse_subscribers = []; sse_lock = threading.Lock()
|
||||||
|
|
||||||
|
def gpu_active_count(model):
|
||||||
|
"""Get number of in-flight requests for a GPU."""
|
||||||
|
if r:
|
||||||
|
return int(r.get("active:" + model) or 0)
|
||||||
|
return 0
|
||||||
|
|
||||||
|
def gpu_incr(model):
|
||||||
|
if r: r.incr("active:" + model)
|
||||||
|
|
||||||
|
def gpu_decr(model):
|
||||||
|
if r:
|
||||||
|
v = r.decr("active:" + model)
|
||||||
|
if v and int(v) < 0:
|
||||||
|
r.set("active:" + model, 0) # never go negative
|
||||||
|
|
||||||
|
def check_gpu_health(model):
|
||||||
|
url = GPU_SIDECARS.get(model)
|
||||||
|
if not url: return {"status": "unknown"}
|
||||||
|
try:
|
||||||
|
resp = requests.get(url, timeout=5)
|
||||||
|
if resp.status_code == 200:
|
||||||
|
d = resp.json()
|
||||||
|
pct = (d.get("vram_used_mb",0) / max(d.get("vram_total_mb",1), 1)) * 100
|
||||||
|
status = "healthy" if pct < 90 else "saturated"
|
||||||
|
# Also check if llama.cpp endpoint is actually responding
|
||||||
|
gpu_url = GPU_URLS.get(model, "")
|
||||||
|
try:
|
||||||
|
hr = requests.get(gpu_url.replace("/v1","") + "/health", headers={"Authorization": "Bearer not-needed"}, timeout=3)
|
||||||
|
if hr.status_code != 200:
|
||||||
|
status = "down"
|
||||||
|
except Exception:
|
||||||
|
status = "down"
|
||||||
|
return {"status": status, "vram_used_mb": d.get("vram_used_mb"), "vram_total_mb": d.get("vram_total_mb"), "vram_pct": round(pct,1), "temp_c": d.get("temp_c"), "gpu_util_pct": d.get("gpu_util_pct"), "gpu_name": d.get("gpu_name"), "power_w": d.get("power_w"), "power_limit_w": d.get("power_limit_w")}
|
||||||
|
except Exception: pass
|
||||||
|
return {"status": "down"}
|
||||||
|
|
||||||
|
def available_models(): return [m for m in GPU_URLS if check_gpu_health(m)["status"] in ("healthy","saturated")]
|
||||||
|
|
||||||
|
def estimate_tokens(msgs): return sum(len(str(m.get("content",""))) for m in msgs) // 4
|
||||||
|
|
||||||
|
def is_gpu_busy(model):
|
||||||
|
"""Check if GPU is at or near max concurrent capacity."""
|
||||||
|
active = gpu_active_count(model)
|
||||||
|
max_c = GPU_MAX_CONCURRENT.get(model, 1)
|
||||||
|
return active >= max_c
|
||||||
|
|
||||||
|
def select_best_gpu(candidates, reason):
|
||||||
|
"""Pick the best GPU from candidates, preferring least-loaded."""
|
||||||
|
best = None
|
||||||
|
best_load = 999
|
||||||
|
for m in candidates:
|
||||||
|
load = gpu_active_count(m)
|
||||||
|
if load < best_load:
|
||||||
|
best_load = load
|
||||||
|
best = m
|
||||||
|
if best:
|
||||||
|
actual_reason = reason
|
||||||
|
if is_gpu_busy(best):
|
||||||
|
actual_reason = "load_balanced_" + reason
|
||||||
|
return {"model": best, "reason": actual_reason}
|
||||||
|
return None
|
||||||
|
|
||||||
|
def route(rd, tier):
|
||||||
|
msgs = rd.get("messages",[]); t = estimate_tokens(msgs)
|
||||||
|
sys = any(m.get("role")=="system" for m in msgs)
|
||||||
|
turns = len([m for m in msgs if m.get("role") in ("user","assistant")])
|
||||||
|
hints = rd.get("routing_hints",{})
|
||||||
|
allowed = TIER_MODELS.get(tier, ["qwen3.5-9b-vlm"])
|
||||||
|
avail = [m for m in available_models() if m in allowed]
|
||||||
|
if not avail: return {"model": allowed[0], "reason": "all_saturated", "saturated": True}
|
||||||
|
|
||||||
|
req = rd.get("model","auto")
|
||||||
|
if req != "auto":
|
||||||
|
target = req if req in avail else avail[0]
|
||||||
|
# If explicit model is busy, check if another can take it
|
||||||
|
if is_gpu_busy(target) and req in allowed:
|
||||||
|
alts = [m for m in avail if m != target and m in allowed]
|
||||||
|
if alts:
|
||||||
|
alt = select_best_gpu(alts, "explicit")
|
||||||
|
if alt: return alt
|
||||||
|
return {"model": target, "reason": "explicit"}
|
||||||
|
|
||||||
|
if hints:
|
||||||
|
if hints.get("priority")=="speed" and "qwen3.5-9b-vlm" in avail:
|
||||||
|
return select_best_gpu(["qwen3.5-9b-vlm"], "hint_speed") or {"model":"qwen3.5-9b-vlm","reason":"hint_speed"}
|
||||||
|
if hints.get("priority")=="quality" and "qwen3.6-27B-code" in avail:
|
||||||
|
return select_best_gpu(["qwen3.6-27B-code"], "hint_quality") or {"model":"qwen3.6-27B-code","reason":"hint_quality"}
|
||||||
|
|
||||||
|
# Heavy -> dense (but fall back to MoE if dense is busy)
|
||||||
|
if t > 4000 or sys or turns > 6:
|
||||||
|
candidates = ["qwen3.6-27B-code","qwen3.6-35B-A3B","qwen3.5-9b-vlm"]
|
||||||
|
candidates = [m for m in candidates if m in avail]
|
||||||
|
result = select_best_gpu(candidates, "heavy_reasoning")
|
||||||
|
if result: return result
|
||||||
|
|
||||||
|
# Ultra-light -> VLM
|
||||||
|
first_msg = msgs[0].get("content","") if msgs else ""
|
||||||
|
words = len(first_msg.split()) if isinstance(first_msg, str) else 99
|
||||||
|
if words <= 3 and turns <= 1 and not sys and "qwen3.5-9b-vlm" in avail:
|
||||||
|
if not is_gpu_busy("qwen3.5-9b-vlm"):
|
||||||
|
return {"model":"qwen3.5-9b-vlm","reason":"ultra_light"}
|
||||||
|
|
||||||
|
# Default: MoE, fall back to dense if MoE is busy
|
||||||
|
if "qwen3.6-35B-A3B" in avail:
|
||||||
|
if is_gpu_busy("qwen3.6-35B-A3B") and "qwen3.6-27B-code" in avail:
|
||||||
|
return {"model": "qwen3.6-27B-code", "reason": "load_balanced_default"}
|
||||||
|
return {"model":"qwen3.6-35B-A3B","reason":"default_moe"}
|
||||||
|
|
||||||
|
return {"model":avail[0],"reason":"fallback"}
|
||||||
|
|
||||||
|
def clean_unicode(text):
|
||||||
|
if not isinstance(text, str): return text
|
||||||
|
text = text.replace(chr(0x2014), "-"); text = text.replace(chr(0x2013), "-")
|
||||||
|
text = text.replace(chr(0x2018), "'"); text = text.replace(chr(0x2019), "'")
|
||||||
|
text = text.replace(chr(0x201C), '"'); text = text.replace(chr(0x201D), '"')
|
||||||
|
text = text.replace(chr(0x2026), "..."); text = text.replace(chr(0x00A0), " ")
|
||||||
|
return text.encode("ascii", "ignore").decode("ascii")
|
||||||
|
|
||||||
|
def clean_response(d):
|
||||||
|
if isinstance(d, dict): return {k: clean_response(v) for k,v in d.items()}
|
||||||
|
if isinstance(d, list): return [clean_response(v) for v in d]
|
||||||
|
if isinstance(d, str): return clean_unicode(d)
|
||||||
|
return d
|
||||||
|
|
||||||
|
def get_metrics():
|
||||||
|
d = {"gpus":[],"route_counts":{},"agent_counts":{},"tier_counts":{},"recent":[],"timestamp":time.time(),"active_requests":{}}
|
||||||
|
for m in GPU_URLS:
|
||||||
|
h = check_gpu_health(m)
|
||||||
|
d["gpus"].append({"id":m,"gpu_name":h.get("gpu_name",m),"status":h.get("status"),"vram_used_mb":h.get("vram_used_mb"),"vram_total_mb":h.get("vram_total_mb"),"vram_pct":h.get("vram_pct"),"temp_c":h.get("temp_c"),"gpu_util_pct":h.get("gpu_util_pct"),"power_w":h.get("power_w"),"power_limit_w":h.get("power_limit_w"),"active_requests":gpu_active_count(m), "max_concurrent": GPU_MAX_CONCURRENT.get(m, 1)})
|
||||||
|
d["active_requests"][m] = gpu_active_count(m)
|
||||||
|
if r:
|
||||||
|
try:
|
||||||
|
for m in GPU_URLS: d["route_counts"][m] = int(r.get("routes:"+m) or 0)
|
||||||
|
for k,v in API_KEYS.items():
|
||||||
|
c = int(r.get("routes:agent:"+v["agent"]) or 0)
|
||||||
|
if c>0: d["agent_counts"][v["agent"]] = c
|
||||||
|
for t in TIER_MODELS: d["tier_counts"][t] = int(r.get("routes:tier:"+t) or 0)
|
||||||
|
raw = r.lrange("routes:recent",0,49)
|
||||||
|
d["recent"] = [json.loads(x) for x in raw] if raw else []
|
||||||
|
except Exception: pass
|
||||||
|
return d
|
||||||
|
|
||||||
|
def bcast():
|
||||||
|
data = get_metrics(); payload = json.dumps(data)
|
||||||
|
with sse_lock:
|
||||||
|
dead = []
|
||||||
|
for q in sse_subscribers:
|
||||||
|
try: q.put(payload)
|
||||||
|
except Exception: dead.append(q)
|
||||||
|
for q in dead: sse_subscribers.remove(q)
|
||||||
|
|
||||||
|
@app.route("/v1/chat/completions", methods=["POST"])
|
||||||
|
def chat():
|
||||||
|
try:
|
||||||
|
rd = request.get_json(force=True)
|
||||||
|
ak = request.headers.get("Authorization","").replace("Bearer ","")
|
||||||
|
ki = API_KEYS.get(ak, {"tier":"starter","agent":"unknown"})
|
||||||
|
tier, agent = ki["tier"], ki["agent"]
|
||||||
|
d = route(rd, tier)
|
||||||
|
if d.get("saturated"):
|
||||||
|
resp = jsonify({"error": "All GPUs saturated", "retry_after_s": 5})
|
||||||
|
resp.headers["Retry-After"] = "5"
|
||||||
|
return resp, 503
|
||||||
|
model, reason, url = d["model"], d["reason"], GPU_URLS[d["model"]]
|
||||||
|
is_stream = rd.get("stream", False)
|
||||||
|
|
||||||
|
gpu_incr(model)
|
||||||
|
decremented = False
|
||||||
|
|
||||||
|
log.info("ROUTE: %s -> %s (%s) stream=%s active=%d/%d", agent, model, reason, is_stream, gpu_active_count(model), GPU_MAX_CONCURRENT.get(model,1))
|
||||||
|
if r:
|
||||||
|
try:
|
||||||
|
r.incr("routes:"+model); r.incr("routes:tier:"+tier); r.incr("routes:agent:"+agent)
|
||||||
|
r.incr("ts:"+model+":"+time.strftime("%Y%m%d%H"))
|
||||||
|
r.lpush("routes:recent", json.dumps({"ts":time.time(),"model":model,"reason":reason,"tier":tier,"agent":agent}))
|
||||||
|
r.ltrim("routes:recent",0,999)
|
||||||
|
except Exception: pass
|
||||||
|
start = time.time()
|
||||||
|
resp = requests.post(url+"/chat/completions", json=rd,
|
||||||
|
headers={"Content-Type":"application/json","Authorization":"Bearer not-needed"}, timeout=300, stream=is_stream)
|
||||||
|
lat = int((time.time()-start)*1000)
|
||||||
|
gpu_decr(model)
|
||||||
|
decremented = True # Release slot
|
||||||
|
|
||||||
|
if resp.status_code != 200: return jsonify({"error":"GPU error "+str(resp.status_code)}), 502
|
||||||
|
if is_stream:
|
||||||
|
def gen():
|
||||||
|
for raw in resp.iter_content(chunk_size=None, decode_unicode=True):
|
||||||
|
if raw: yield clean_unicode(raw)
|
||||||
|
bcast()
|
||||||
|
return Response(stream_with_context(gen()), mimetype="text/event-stream")
|
||||||
|
data = clean_response(resp.json())
|
||||||
|
for c in data.get("choices",[]):
|
||||||
|
msg = c.get("message",{})
|
||||||
|
if not msg.get("content") and msg.get("reasoning_content"):
|
||||||
|
msg["content"] = msg["reasoning_content"]
|
||||||
|
data["routing"] = {"model":model,"reason":reason,"gpu":url,"tier":tier,"agent":agent,"latency_ms":lat,"active_gpu":gpu_active_count(model)}
|
||||||
|
bcast()
|
||||||
|
return jsonify(data)
|
||||||
|
if not decremented:
|
||||||
|
try: gpu_decr(model)
|
||||||
|
except: pass
|
||||||
|
except requests.Timeout:
|
||||||
|
return jsonify({"error":"timeout"}), 504
|
||||||
|
log.error("Error: %s\n%s", e, traceback.format_exc())
|
||||||
|
return jsonify({"error":str(e)}), 500
|
||||||
|
|
||||||
|
@app.route("/v1/models")
|
||||||
|
def models(): return jsonify({"object":"list","data":[{"id":m,"object":"model","owned_by":"syslog","status":check_gpu_health(m).get("status"),"gpu":check_gpu_health(m).get("gpu_name")} for m in GPU_URLS]})
|
||||||
|
|
||||||
|
@app.route("/health")
|
||||||
|
def health():
|
||||||
|
gpus = {}
|
||||||
|
for m in GPU_URLS:
|
||||||
|
h = check_gpu_health(m)
|
||||||
|
h["active_requests"] = gpu_active_count(m)
|
||||||
|
h["max_concurrent"] = GPU_MAX_CONCURRENT.get(m, 1)
|
||||||
|
gpus[m] = h
|
||||||
|
return jsonify({"status":"healthy","redis":"connected" if r else "down","gpus":gpus,"available_models":available_models()})
|
||||||
|
|
||||||
|
@app.route("/metrics")
|
||||||
|
def metrics(): return jsonify(get_metrics())
|
||||||
|
|
||||||
|
@app.route("/metrics/timeseries")
|
||||||
|
def metrics_timeseries():
|
||||||
|
period = request.args.get("period", "day"); models_list = list(GPU_URLS.keys())
|
||||||
|
data = {"models": {}, "labels": []}
|
||||||
|
if period == "day":
|
||||||
|
buckets = [time.strftime("%Y%m%d%H", time.gmtime(time.time()-h*3600)) for h in range(23,-1,-1)]
|
||||||
|
data["labels"] = [time.strftime("%H:00", time.gmtime(time.time()-h*3600)) for h in range(23,-1,-1)]
|
||||||
|
elif period == "week":
|
||||||
|
buckets = [time.strftime("%Y%m%d", time.gmtime(time.time()-d*86400)) for d in range(6,-1,-1)]
|
||||||
|
data["labels"] = [time.strftime("%a", time.gmtime(time.time()-d*86400)) for d in range(6,-1,-1)]
|
||||||
|
else:
|
||||||
|
buckets = [time.strftime("%Y%m%d", time.gmtime(time.time()-d*86400)) for d in range(29,-1,-1)]
|
||||||
|
data["labels"] = [time.strftime("%m/%d", time.gmtime(time.time()-d*86400)) for d in range(29,-1,-1)]
|
||||||
|
if r:
|
||||||
|
for model in models_list:
|
||||||
|
counts = []
|
||||||
|
for bucket in buckets:
|
||||||
|
total = 0
|
||||||
|
if period in ("week","month"):
|
||||||
|
for hh in range(24): total += int(r.get("ts:"+model+":"+bucket+"{:02d}".format(hh)) or 0)
|
||||||
|
else: total = int(r.get("ts:"+model+":"+bucket) or 0)
|
||||||
|
counts.append(total)
|
||||||
|
data["models"][model] = counts
|
||||||
|
return jsonify(data)
|
||||||
|
|
||||||
|
@app.route("/stream")
|
||||||
|
def stream():
|
||||||
|
def ev():
|
||||||
|
q = queue.Queue()
|
||||||
|
with sse_lock: sse_subscribers.append(q)
|
||||||
|
try:
|
||||||
|
yield "data: "+json.dumps(get_metrics())+"\n\n"
|
||||||
|
while True:
|
||||||
|
try: yield "data: "+q.get(timeout=3)+"\n\n"
|
||||||
|
except queue.Empty: yield "data: "+json.dumps(get_metrics())+"\n\n"
|
||||||
|
except GeneratorExit: pass
|
||||||
|
finally:
|
||||||
|
with sse_lock:
|
||||||
|
if q in sse_subscribers: sse_subscribers.remove(q)
|
||||||
|
return Response(stream_with_context(ev()), mimetype="text/event-stream",
|
||||||
|
headers={"Cache-Control":"no-cache","X-Accel-Buffering":"no","Access-Control-Allow-Origin":"*"})
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
log.info("Router on :9000 (load-aware)")
|
||||||
|
app.run(host="0.0.0.0", port=9000, debug=False)
|
||||||
@@ -0,0 +1,80 @@
|
|||||||
|
# Add time-series tracking and endpoint to router
|
||||||
|
with open('/opt/inference-harness/router/router.py') as f:
|
||||||
|
code = f.read()
|
||||||
|
|
||||||
|
# Add time-series tracking in the chat handler (after Redis incr)
|
||||||
|
old_track = '''r.incr('routes:'+model); r.incr('routes:tier:'+tier); r.incr('routes:agent:'+agent)
|
||||||
|
r.lpush('routes:recent', json.dumps'''
|
||||||
|
new_track = '''r.incr('routes:'+model); r.incr('routes:tier:'+tier); r.incr('routes:agent:'+agent)
|
||||||
|
# Time-series: hourly bucket
|
||||||
|
hour_key = 'ts:'+model+':'+time.strftime('%Y%m%d%H')
|
||||||
|
r.incr(hour_key)
|
||||||
|
r.expire(hour_key, 86400*31) # keep 31 days
|
||||||
|
r.lpush('routes:recent', json.dumps'''
|
||||||
|
|
||||||
|
code = code.replace(old_track, new_track)
|
||||||
|
|
||||||
|
# Add /metrics/timeseries endpoint before if __name__
|
||||||
|
ts_endpoint = '''
|
||||||
|
@app.route('/metrics/timeseries')
|
||||||
|
def metrics_timeseries():
|
||||||
|
period = request.args.get('period', 'day')
|
||||||
|
models = list(GPU_URLS.keys())
|
||||||
|
data = {'models': {}, 'labels': []}
|
||||||
|
|
||||||
|
if period == 'day':
|
||||||
|
# Last 24 hours, hourly buckets
|
||||||
|
buckets = []
|
||||||
|
for h in range(23, -1, -1):
|
||||||
|
t = time.time() - h * 3600
|
||||||
|
buckets.append(time.strftime('%Y%m%d%H', time.gmtime(t)))
|
||||||
|
data['labels'] = [time.strftime('%H:00', time.gmtime(time.time() - h*3600)) for h in range(23, -1, -1)]
|
||||||
|
elif period == 'week':
|
||||||
|
# Last 7 days, daily buckets
|
||||||
|
buckets = []
|
||||||
|
for d in range(6, -1, -1):
|
||||||
|
t = time.time() - d * 86400
|
||||||
|
buckets.append(time.strftime('%Y%m%d', time.gmtime(t)))
|
||||||
|
data['labels'] = [time.strftime('%a', time.gmtime(time.time() - d*86400)) for d in range(6, -1, -1)]
|
||||||
|
else:
|
||||||
|
# Month — last 30 days, 3-day buckets
|
||||||
|
buckets = []
|
||||||
|
for d in range(29, -1, -3):
|
||||||
|
t = time.time() - d * 86400
|
||||||
|
buckets.append(time.strftime('%Y%m%d', time.gmtime(t)))
|
||||||
|
data['labels'] = [time.strftime('%m/%d', time.gmtime(time.time() - d*86400)) for d in range(29, -1, -3)]
|
||||||
|
|
||||||
|
if r:
|
||||||
|
for model in models:
|
||||||
|
counts = []
|
||||||
|
for bucket in buckets:
|
||||||
|
if period == 'month':
|
||||||
|
# Sum 3 consecutive days per bucket
|
||||||
|
total = 0
|
||||||
|
base = time.strptime(bucket, '%Y%m%d')
|
||||||
|
for offset in range(3):
|
||||||
|
d = time.strftime('%Y%m%d', time.gmtime(time.mktime(base) + offset*86400))
|
||||||
|
total += int(r.get('ts:'+model+':'+d) or 0)
|
||||||
|
# Also check hourly keys for today
|
||||||
|
for hh in range(24):
|
||||||
|
total += int(r.get('ts:'+model+':'+d+'{:02d}'.format(hh)) or 0)
|
||||||
|
counts.append(total)
|
||||||
|
else:
|
||||||
|
key = 'ts:'+model+':'+bucket
|
||||||
|
if period == 'week':
|
||||||
|
# Sum all hours in the day
|
||||||
|
total = sum(int(r.get(key+'{:02d}'.format(h)) or 0) for h in range(24))
|
||||||
|
else:
|
||||||
|
total = int(r.get(key) or 0)
|
||||||
|
counts.append(total)
|
||||||
|
data['models'][model] = counts
|
||||||
|
|
||||||
|
return jsonify(data)
|
||||||
|
'''
|
||||||
|
|
||||||
|
# Insert before if __name__
|
||||||
|
code = code.replace(if __name__ == __main__:, ts_endpoint + nif __name__ == __main__:)
|
||||||
|
|
||||||
|
with open('/opt/inference-harness/router/router.py', 'w') as f:
|
||||||
|
f.write(code)
|
||||||
|
print('Time-series tracking and endpoint added')
|
||||||
Reference in New Issue
Block a user