LLM Analytics API

GET /api/analytics/llm

Returns aggregated LLM call metrics: summary statistics, per-model breakdown, and time-bucketed series.

Query Parameters

Parameter	Type	Default	Description
from	string	24h ago	Start of time range (ISO 8601)
to	string	now	End of time range (ISO 8601)
granularity	string	hour	Bucket size: hour, day, or week
agentId	string	—	Filter to a specific agent
model	string	—	Filter to a specific model
provider	string	—	Filter to a specific provider

Response (200)

{
  "summary": {
    "totalCalls": 42,
    "totalCostUsd": 12.34,
    "totalInputTokens": 150000,
    "totalOutputTokens": 50000,
    "avgLatencyMs": 1250,
    "avgCostPerCall": 0.29
  },
  "byModel": [
    {
      "provider": "anthropic",
      "model": "claude-sonnet-4-20250514",
      "calls": 20,
      "costUsd": 8.50,
      "inputTokens": 100000,
      "outputTokens": 30000,
      "avgLatencyMs": 1500
    },
    {
      "provider": "openai",
      "model": "gpt-4o",
      "calls": 15,
      "costUsd": 3.00,
      "inputTokens": 35000,
      "outputTokens": 15000,
      "avgLatencyMs": 900
    }
  ],
  "byTime": [
    {
      "bucket": "2026-02-08T10:00:00Z",
      "calls": 5,
      "costUsd": 1.20,
      "inputTokens": 15000,
      "outputTokens": 5000,
      "avgLatencyMs": 900
    },
    {
      "bucket": "2026-02-08T11:00:00Z",
      "calls": 8,
      "costUsd": 2.10,
      "inputTokens": 25000,
      "outputTokens": 8000,
      "avgLatencyMs": 1100
    }
  ]
}

Response Fields

summary

Field	Type	Description
totalCalls	number	Total number of LLM calls
totalCostUsd	number	Total cost in USD
totalInputTokens	number	Total input/prompt tokens
totalOutputTokens	number	Total output/completion tokens
avgLatencyMs	number	Average latency in milliseconds
avgCostPerCall	number	Average cost per call in USD

byModel[]

Field	Type	Description
provider	string	Provider name
model	string	Model identifier
calls	number	Number of calls to this model
costUsd	number	Total cost for this model
inputTokens	number	Total input tokens for this model
outputTokens	number	Total output tokens for this model
avgLatencyMs	number	Average latency for this model

byTime[]

Field	Type	Description
bucket	string	Time bucket start (ISO 8601)
calls	number	Calls in this bucket
costUsd	number	Cost in this bucket
inputTokens	number	Input tokens in this bucket
outputTokens	number	Output tokens in this bucket
avgLatencyMs	number	Average latency in this bucket

curl Example

# Get LLM analytics for the past week, by day
curl "http://localhost:3400/api/analytics/llm?from=2026-02-01&to=2026-02-08&granularity=day" \
  -H "Authorization: Bearer als_your_key"

# Filter to a specific model
curl "http://localhost:3400/api/analytics/llm?model=claude-sonnet-4-20250514&from=2026-02-01" \
  -H "Authorization: Bearer als_your_key"

# Filter by agent and provider
curl "http://localhost:3400/api/analytics/llm?agentId=my-agent&provider=anthropic" \
  -H "Authorization: Bearer als_your_key"

SDK Example

import { AgentLensClient } from '@agentlensai/sdk';

const client = new AgentLensClient({
  url: 'http://localhost:3400',
  apiKey: 'als_your_key',
});

// Get full analytics
const analytics = await client.getLlmAnalytics({
  from: '2026-02-01',
  to: '2026-02-08',
  granularity: 'day',
});

console.log(`Total LLM calls: ${analytics.summary.totalCalls}`);
console.log(`Total cost: $${analytics.summary.totalCostUsd.toFixed(2)}`);
console.log(`Average latency: ${analytics.summary.avgLatencyMs}ms`);

// Per-model breakdown
for (const model of analytics.byModel) {
  console.log(`${model.provider}/${model.model}: ${model.calls} calls, $${model.costUsd.toFixed(2)}`);
}

CLI Example

# Summary stats
agentlens llm stats

# Per-model breakdown
agentlens llm models --from 2026-02-01

# Recent calls
agentlens llm recent --model claude-sonnet-4-20250514

See the LLM Call Tracking guide for full documentation.