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next-ai-draw-io/app/api/log-save/route.ts

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import { randomUUID } from "crypto"
import { z } from "zod"
import { getLangfuseClient } from "@/lib/langfuse"
const saveSchema = z.object({
filename: z.string().min(1).max(255),
format: z.enum(["drawio", "png", "svg"]),
sessionId: z.string().min(1).max(200).optional(),
})
export async function POST(req: Request) {
const langfuse = getLangfuseClient()
if (!langfuse) {
return Response.json({ success: true, logged: false })
}
// Validate input
let data
try {
data = saveSchema.parse(await req.json())
} catch {
return Response.json(
{ success: false, error: "Invalid input" },
{ status: 400 },
)
}
const { filename, format, sessionId } = data
try {
const timestamp = new Date().toISOString()
// Find the most recent chat trace for this session to attach the save flag
const tracesResponse = await langfuse.api.trace.list({
sessionId,
limit: 1,
})
const traces = tracesResponse.data || []
const latestTrace = traces[0]
if (latestTrace) {
// Add a score to the existing trace to flag that user saved
await langfuse.api.ingestion.batch({
batch: [
{
type: "score-create",
id: randomUUID(),
timestamp,
body: {
id: randomUUID(),
traceId: latestTrace.id,
name: "diagram-saved",
value: 1,
comment: `User saved diagram as ${filename}.${format}`,
},
},
],
})
}
// If no trace found, skip logging (user hasn't chatted yet)
return Response.json({ success: true, logged: !!latestTrace })
} catch (error) {
console.error("Langfuse save error:", error)
return Response.json(
{ success: false, error: "Failed to log save" },
{ status: 500 },
)
}
}