Files
next-ai-draw-io/lib/langfuse.ts
T
dayuan.jiang 366480426d fix(chat): close credential leaks and harden the chat route
- Vertex: a client-supplied base URL only works with the client's own Vertex key
- Accept only data: URLs for file parts in every message, so the server never downloads them
- Output budget retry accounts for the thinking budget Bedrock/Anthropic add, and reads
  Volcengine, DashScope, SGLang and vLLM rejections; falls back to 16000 once
- x-max-output-tokens can only lower the budget on server credentials
- On server credentials only server models or AI_MODEL entries can be used
- Drop tool results together with the invalid tool calls they belong to
- Count quota tokens as input + output (cached tokens were counted twice)
- Private-URL check for custom base URLs, end Langfuse traces on error/abort/early return
- Fix repairToolCall ordering and placeholder, align edit_diagram prompt with operations
- Panel Bedrock keys are read from ADMIN_AWS_*; forward the access code to EdgeOne
- isMinimalDiagram only treats root cells as an empty canvas
2026-10-03 17:45:41 +09:00

97 lines
2.6 KiB
TypeScript

import { LangfuseClient } from "@langfuse/client"
import { observe, updateActiveTrace } from "@langfuse/tracing"
import * as api from "@opentelemetry/api"
// Singleton LangfuseClient instance for direct API calls
let langfuseClient: LangfuseClient | null = null
export function getLangfuseClient(): LangfuseClient | null {
if (!process.env.LANGFUSE_PUBLIC_KEY || !process.env.LANGFUSE_SECRET_KEY) {
return null
}
if (!langfuseClient) {
langfuseClient = new LangfuseClient({
publicKey: process.env.LANGFUSE_PUBLIC_KEY,
secretKey: process.env.LANGFUSE_SECRET_KEY,
baseUrl: process.env.LANGFUSE_BASEURL,
})
}
return langfuseClient
}
// Check if Langfuse is configured (both keys required)
export function isLangfuseEnabled(): boolean {
return !!(
process.env.LANGFUSE_PUBLIC_KEY && process.env.LANGFUSE_SECRET_KEY
)
}
// Update trace with input data at the start of request
export function setTraceInput(params: {
input: string
sessionId?: string
userId?: string
}) {
if (!isLangfuseEnabled()) return
updateActiveTrace({
name: "chat",
input: params.input,
sessionId: params.sessionId,
userId: params.userId,
})
}
// Update trace with output and end the span
// Note: AI SDK 6 telemetry automatically reports token usage on its spans,
// so we only need to set the output text and close our wrapper span
export function setTraceOutput(output: string) {
if (!isLangfuseEnabled()) return
updateActiveTrace({ output })
endTrace()
}
// End the observe() wrapper span (AI SDK creates its own child spans with usage).
// It uses endOnExit: false, so every request path has to end it, or the trace
// is never exported: stream finish, stream error/abort, and early returns.
export function endTrace() {
if (!isLangfuseEnabled()) return
const activeSpan = api.trace.getActiveSpan()
if (activeSpan) {
activeSpan.end()
}
}
// Get telemetry config for streamText
export function getTelemetryConfig(params: {
sessionId?: string
userId?: string
}) {
if (!isLangfuseEnabled()) return undefined
return {
isEnabled: true,
recordInputs: true,
recordOutputs: true,
metadata: {
sessionId: params.sessionId,
userId: params.userId,
},
}
}
// Wrap a handler with Langfuse observe
export function wrapWithObserve<T>(
handler: (req: Request) => Promise<T>,
): (req: Request) => Promise<T> {
if (!isLangfuseEnabled()) {
return handler
}
return observe(handler, { name: "chat", endOnExit: false })
}