55 lines
2.4 KiB
Bash
Executable File
55 lines
2.4 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Query Z.ai GLM Coding Plan usage (same endpoints as the Claude Code glm-plan-usage plugin).
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# Usage: zai-usage.sh [hours] (default: 24h lookback window)
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set -euo pipefail
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HOURS="${1:-24}"
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AUTH_JSON="$HOME/.pi/agent/auth.json"
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export KEY="$(python3 -c "import json;print(json.load(open('$AUTH_JSON'))['zai']['key'])")"
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BASE="https://api.z.ai/api/monitor/usage"
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NOW="$(date -u +'%Y-%m-%d %H:%M:%S')"
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START="$(date -u -d "$HOURS hours ago" +'%Y-%m-%d %H:%M:%S')"
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Q="startTime=$(python3 -c "import urllib.parse,sys;print(urllib.parse.quote(sys.argv[1]))" "$START")&endTime=$(python3 -c "import urllib.parse,sys;print(urllib.parse.quote(sys.argv[1]))" "$NOW")"
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fetch() { curl -sS -m 20 "$1" -H "Authorization: $KEY" -H 'Accept-Language: en-US'; }
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python3 - "$BASE" "$Q" <<'EOF'
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import json, subprocess, sys
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from datetime import datetime, timezone
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base, q = sys.argv[1], sys.argv[2]
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def fetch(path, params=""):
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out = subprocess.run(["curl", "-sS", "-m", "20", f"{base}/{path}{params}",
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"-H", f"Authorization: {__import__('os').environ.get('KEY','')}"],
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capture_output=True, text=True, env={**__import__('os').environ}).stdout
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return json.loads(out).get("data")
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# Quota / limits
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data = fetch("quota/limit")
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level = data.get("level", "?")
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print(f"Plan: {level.upper()}\n")
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for lim in data.get("limits", []):
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if lim["type"] != "CREDIT_LIMIT":
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continue
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unit = "5-hour" if lim["unit"] == 3 else ("weekly" if lim["unit"] == 6 else f"unit{lim['unit']}")
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reset = datetime.fromtimestamp(lim["nextResetTime"] / 1000, tz=timezone.utc)
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delta = reset - datetime.now(timezone.utc)
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hrs = int(delta.total_seconds() // 3600); mins = int(delta.total_seconds() % 3600 // 60)
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when = f"in {hrs}h{mins:02d}m" if hrs else f"in {mins}m"
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print(f"{unit:>7} credits: {lim['currentValue']:>6} / {lim['usage']} used ({lim['percentage']}%)"
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f" — remaining {lim['remaining']}, resets {when}")
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# Model usage in window
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data = fetch("model-usage", f"?{q}")
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tot = data.get("totalUsage", {})
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print(f"\nLast window: {tot.get('totalModelCallCount', 0)} model calls")
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for m in tot.get("modelSummaryList", []):
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print(f" {m['modelName']}: {m['totalTokens']:,} tokens")
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tools = fetch("tool-usage", f"?{q}").get("totalUsage", {})
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ncalls = tools.get("totalNetworkSearchCount", 0) + tools.get("totalWebReadMcpCount", 0) + tools.get("totalZreadMcpCount", 0)
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print(f"MCP tool calls: {ncalls}")
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EOF
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