phattbeats LiteLLM CLI
Python CLI for the LiteLLM proxy at 10.0.0.100:4000. REST API only — no browser scraping, no external deps.
What this gives you: Daily spend by model, total spend, health status, model pricing, key management.
What this does NOT give you: Per-request token counts, real-time usage logs, input vs output token breakdowns. LiteLLM's REST API doesn't expose those without an Enterprise license. The UI at /ui/logs shows them but requires browser automation which is fragile.
Quick Reference
litellm.py overview # Health + spend snapshot
litellm.py health # Backend health check
litellm.py spend [--days N] # Spend by date (default: 7 days)
litellm.py usage [--days N] # Token counts by day + model (REST API)
litellm.py models # Model list + per-1M-token pricing
litellm.py global-spend # Lifetime total spend
litellm.py users # Per-user spend breakdown
litellm.py logs [--limit N] # Per-request logs (UI scraping, ~30s)
litellm.py keys list # List API keys
litellm.py keys create ALIAS # Create new key
litellm.py keys delete KEY # Delete a key
Setup
export LITELLM_URL="http://10.0.0.100:4000"
export LITELLM_KEY="<MASTER_KEY from TOOLS.md>"
Hardcoded defaults work without env vars.
Output
Auto-detects: JSON when piped, human-readable in terminal. Force JSON with --json.
JSON envelope:
{"ok": true, "command": "spend", "result": {...}}
Workflows
Check token usage by day and model
litellm.py usage --days 7
Daily token counts (prompt + completion + cache), per-model breakdown, request counts. Fast — uses REST API, no scraping.
Check per-request details (slow)
litellm.py logs --limit 10
Scrapes the LiteLLM UI via browserless (~30s). Shows per-request: status, cost, latency, ttft, model, and full token breakdown (input + output). This is the only way to get per-request token counts without Enterprise.
Quick cost check
litellm.py overview
Health + today's spend + week spend + total.
Where did the money go?
litellm.py spend --days 7
Daily breakdown + per-model spend. Aggregated by day, not per-request.
What models do we have and what do they cost?
litellm.py models
Input/output pricing per 1M tokens from the model registry.
Is LiteLLM healthy?
litellm.py health
Backend connectivity + model health counts.
Create an API key
litellm.py keys create my-key --duration 30d --models claude-sonnet-4-6
How Token Counts Work
Three tiers of data:
usage (recommended): REST API via /user/daily/activity. Fast (<1s). Daily token counts by model — prompt, completion, cache, total. Request counts (success/fail). This is the sweet spot for most queries.
spend/overview: REST API via /spend/logs. Instant. Daily spend by model. No token counts, just dollars.
logs: UI scraping via browserless. Slow (~30s). Per-request: tokens, cost, latency, model, status. Only needed when you want to inspect individual requests.
Use usage for "how many tokens did we burn" — it's fast and has the data. Use logs only when you need request-level detail.
Related: Budget Alerts
The litellm-monitor skill handles budget threshold alerts via Signal (50/80/95/100%). That's a separate cron-based system. This CLI is for on-demand queries.
Notes
- All spend values in USD
- Date format: YYYY-MM-DD
- Keys are truncated in output (first 12 chars) for security
--jsonauto-activates when stdout is not a TTY- REST API timeout: 10 seconds
- Logs scraping timeout: 45 seconds