Options
createAILogger(log, options?) accepts a single options bag. Every option is opt-in. The defaults stay quiet, and they stay safe: nothing a model was sent or returned reaches your drain until you ask for it by name.
| Option | Type | Default | Description |
|---|---|---|---|
toolInputs | boolean | ToolInputsOptions | false | Capture tool call inputs alongside their names (off by default to avoid leaking sensitive data). |
cost | Record<string, ModelCost> | undefined | Pricing map. Keys are model IDs, values are { input, output } in dollars per 1M tokens. |
Tool Inputs
By default, ai.toolCalls is a string[] of tool names. Enable toolInputs to capture inputs too, which suits debugging agent behaviour or auditing what data the model reached for.
maxLength and transform before raw capture in production.Capture everything
const ai = createAILogger(log, { toolInputs: true })
Truncate long inputs
const ai = createAILogger(log, { toolInputs: { maxLength: 200 } })
Redact sensitive fields
const ai = createAILogger(log, {
toolInputs: {
maxLength: 500,
transform: (input, toolName) => {
if (toolName === 'queryDB') return { sql: '***' }
return input
},
},
})
| Sub-option | Type | Description |
|---|---|---|
maxLength | number | Truncate stringified inputs exceeding this character length (appends …). |
transform | (input, toolName) => unknown | Custom transform applied before maxLength. Use to redact fields or reshape data. |
When toolInputs is enabled, ai.toolCalls becomes an Array<{ name, input }> instead of a plain string array.
Cost Estimation
Pass a cost map to compute estimated dollar cost per call. The middleware multiplies token usage by the per-million rates and sets ai.estimatedCost on the wide event.
const ai = createAILogger(log, {
cost: {
'claude-sonnet-4.6': { input: 3, output: 15 },
'gpt-4o': { input: 2.5, output: 10 },
},
})
Read the result from your handler with ai.getEstimatedCost(), which suits billing dashboards or warning users before expensive calls.
cost map in one file alongside model selection so renaming a model in production also updates pricing. Per-route maps drift the moment two routes disagree about which model they call, so keep one.Error Handling
If a model call fails, the middleware captures the error into the wide event before re-throwing:
{
"ai": {
"calls": 1,
"model": "claude-sonnet-4.6",
"provider": "anthropic",
"finishReason": "error",
"error": "API rate limit exceeded"
}
}
Stream errors (e.g. content filter) are also captured from the stream's error chunks. Your error-handling code (try/catch, route-level error handlers) keeps working as usual, since the middleware only observes.