llama-cpp: xmrig + grafana hooks
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@@ -1,14 +1,42 @@
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#!/usr/bin/env python3
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"""
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Grafana annotation service for llama-cpp inference requests.
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Monitors llama-server CPU usage via /proc. Creates a Grafana annotation
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when inference starts (CPU spikes), closes it when inference ends.
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"""
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import glob
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import json
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import os
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import sys
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import time
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import urllib.request
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LLAMA_CPP_URL = os.environ.get("LLAMA_CPP_URL", "http://127.0.0.1:6688")
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GRAFANA_URL = os.environ.get("GRAFANA_URL", "http://127.0.0.1:3000")
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STATE_FILE = os.environ.get("STATE_FILE", "/var/lib/llama-cpp-annotations/state.json")
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POLL_INTERVAL = int(os.environ.get("POLL_INTERVAL", "5"))
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CPU_THRESHOLD = float(os.environ.get("CPU_THRESHOLD", "50"))
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def find_llama_pid():
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for path in glob.glob("/proc/[0-9]*/comm"):
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try:
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with open(path) as f:
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if f.read().strip() == "llama-server":
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return int(path.split("/")[2])
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except (OSError, ValueError):
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continue
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return None
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def get_cpu_times(pid):
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try:
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with open(f"/proc/{pid}/stat") as f:
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fields = f.read().split(")")[-1].split()
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return int(fields[11]) + int(fields[12])
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except (OSError, IndexError, ValueError):
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return None
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def http_json(method, url, body=None):
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@@ -23,19 +51,6 @@ def http_json(method, url, body=None):
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return json.loads(resp.read())
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def get_slots():
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try:
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req = urllib.request.Request(
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f"{LLAMA_CPP_URL}/slots",
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headers={"Accept": "application/json"},
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)
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with urllib.request.urlopen(req, timeout=5) as resp:
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return json.loads(resp.read())
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except Exception as e:
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print(f"Error fetching slots: {e}", file=sys.stderr)
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return None
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def load_state():
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try:
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with open(STATE_FILE) as f:
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@@ -81,45 +96,58 @@ def grafana_close(grafana_id, end_ms, text=None):
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def main():
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state = load_state()
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prev_ticks = None
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prev_time = None
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hz = os.sysconf("SC_CLK_TCK")
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while True:
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now_ms = int(time.time() * 1000)
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slots = get_slots()
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pid = find_llama_pid()
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if slots is not None:
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# Track which slots are currently processing
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processing_ids = set()
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for slot in slots:
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slot_id = str(slot["id"])
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is_processing = slot.get("is_processing", False)
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if pid is None:
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prev_ticks = None
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prev_time = None
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time.sleep(POLL_INTERVAL)
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continue
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if is_processing:
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processing_ids.add(slot_id)
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if slot_id not in state:
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text = f"LLM request (slot {slot['id']})"
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grafana_id = grafana_post(text, now_ms)
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if grafana_id is not None:
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state[slot_id] = {
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"grafana_id": grafana_id,
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"start_ms": now_ms,
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}
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save_state(state)
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ticks = get_cpu_times(pid)
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now = time.monotonic()
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# Close annotations for slots that stopped processing
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for slot_id in [k for k in state if k not in processing_ids]:
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info = state.pop(slot_id)
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# Try to get token count from the slot data
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n_decoded = None
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for slot in slots:
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if str(slot["id"]) == slot_id:
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n_decoded = slot.get("next_token", {}).get("n_decoded")
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break
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text = f"LLM request (slot {slot_id})"
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if n_decoded is not None and n_decoded > 0:
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text += f" — {n_decoded} tokens"
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grafana_close(info["grafana_id"], now_ms, text)
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if ticks is None or prev_ticks is None or prev_time is None:
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prev_ticks = ticks
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prev_time = now
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time.sleep(POLL_INTERVAL)
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continue
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dt = now - prev_time
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if dt <= 0:
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prev_ticks = ticks
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prev_time = now
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time.sleep(POLL_INTERVAL)
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continue
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cpu_pct = ((ticks - prev_ticks) / hz) / dt * 100
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prev_ticks = ticks
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prev_time = now
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busy = cpu_pct > CPU_THRESHOLD
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if busy and "active" not in state:
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grafana_id = grafana_post("LLM request", now_ms)
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if grafana_id is not None:
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state["active"] = {
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"grafana_id": grafana_id,
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"start_ms": now_ms,
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}
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save_state(state)
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elif not busy and "active" in state:
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info = state.pop("active")
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duration_s = (now_ms - info["start_ms"]) / 1000
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text = f"LLM request ({duration_s:.1f}s)"
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grafana_close(info["grafana_id"], now_ms, text)
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save_state(state)
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time.sleep(POLL_INTERVAL)
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