Skip to main content Manage Langfuse data export, retention, and compliance requirements.
Use when exporting trace data, configuring retention policies,
or implementing data compliance for LLM observability.
Trigger with phrases like "langfuse data export", "langfuse retention",
"langfuse GDPR", "langfuse compliance", "export langfuse traces".
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill langfuse-data-handling ai automation claude-code devops mcp ai-agents
Langfuse Data Handling
Overview
Manage the Langfuse data lifecycle: export traces and scores via the API, configure retention policies, handle GDPR data subject requests, anonymize data for analytics, and maintain audit trails.
Prerequisites
@langfuse/client installedLangfuse API keys with appropriate permissions
Understanding of your compliance requirements (GDPR, SOC2, HIPAA)
Instructions
Step 1: Export Trace Data via API
import { LangfuseClient } from "@langfuse/client";
import { writeFileSync } from "fs";
const langfuse = new LangfuseClient();
async function exportTraces(options: {
fromDate: string;
toDate: string;
outputFile: string;
includeObservations?: boolean;
}) {
const allTraces: any[] = [];
let page = 1;
let hasMore = true;
while (hasMore) {
const result = await langfuse.api.traces.list({
fromTimestamp: options.fromDate,
toTimestamp: options.toDate,
limit: 100,
page,
});
for (const trace of result.data) {
const exportItem: any = {
id: trace.id,
name: trace.name,
timestamp: trace.timestamp,
userId: trace.userId,
sessionId: trace.sessionId,
metadata: trace.metadata,
tags: trace.tags,
};
if (options.includeObservations) {
const observations = await langfuse.api.observations.list({
traceId: trace.id,
});
exportItem.observations = observations.data;
}
allTraces.push(exportItem);
}
hasMore = result.data.length === 100;
page++;
// Rate limit respect
await new Promise((r) => setTimeout(r, 200));
}
writeFileSync(options.outputFile, JSON.stringify(allTraces, null, 2));
console.log(`Exported ${allTraces.length} traces to ${options.outputFile}`);
}
// Usage
await exportTraces({
fromDate: "2025-01-01T00:00:00Z",
toDate: "2025-01-31T23:59:59Z",
outputFile: "traces-january.json",
includeObservations: true,
});
Step 2: Export Scores async function exportScores(fromDate: string, outputFile: string) {
const scores: any[] = [];
let page = 1;
let hasMore = true;
while (hasMore) {
const result = await langfuse.api.scores.list({
fromTimestamp: fromDate,
limit: 100,
page,
});
scores.push(...result.data);
hasMore = result.data.length === 100;
page++;
await new Promise((r) => setTimeout(r, 200));
}
writeFileSync(outputFile, JSON.stringify(scores, null, 2));
console.log(`Exported ${scores.length} scores to ${outputFile}`);
}
Step 3: Data Retention Configuration Self-hosted: Set retention via environment variable:
# docker-compose.yml
services:
langfuse:
environment:
- LANGFUSE_RETENTION_DAYS=90
Cloud: Programmatic cleanup of old data:
async function enforceRetention(maxAgeDays: number) {
const cutoff = new Date(Date.now() - maxAgeDays * 86400000).toISOString();
const oldTraces = await langfuse.api.traces.list({
toTimestamp: cutoff,
limit: 100,
});
console.log(`Found ${oldTraces.data.length} traces older than ${maxAgeDays} days`);
for (const trace of oldTraces.data) {
await langfuse.api.traces.delete(trace.id);
await new Promise((r) => setTimeout(r, 100)); // Rate limit
}
}
// Run as cron job
await enforceRetention(90);
Step 4: GDPR Data Subject Requests // Handle "Right to Access" -- export all data for a user
async function handleAccessRequest(userId: string) {
const traces = await langfuse.api.traces.list({
userId,
limit: 1000,
});
const userData = {
userId,
exportDate: new Date().toISOString(),
traceCount: traces.data.length,
traces: traces.data.map((t) => ({
id: t.id,
name: t.name,
timestamp: t.timestamp,
input: t.input,
output: t.output,
metadata: t.metadata,
})),
};
writeFileSync(`gdpr-export-${userId}.json`, JSON.stringify(userData, null, 2));
return userData;
}
// Handle "Right to Erasure" -- delete all data for a user
async function handleDeletionRequest(userId: string) {
const traces = await langfuse.api.traces.list({
userId,
limit: 1000,
});
let deleted = 0;
for (const trace of traces.data) {
await langfuse.api.traces.delete(trace.id);
deleted++;
await new Promise((r) => setTimeout(r, 100));
}
console.log(`Deleted ${deleted} traces for user ${userId}`);
return { userId, tracesDeleted: deleted };
}
Step 5: Data Anonymization for Analytics import crypto from "crypto";
function anonymizeTrace(trace: any): any {
return {
...trace,
userId: trace.userId ? crypto.createHash("sha256").update(trace.userId).digest("hex").slice(0, 16) : null,
sessionId: trace.sessionId ? crypto.createHash("sha256").update(trace.sessionId).digest("hex").slice(0, 16) : null,
input: "[REDACTED]",
output: "[REDACTED]",
metadata: {
model: trace.metadata?.model,
// Keep operational fields, remove PII
},
};
}
async function exportAnonymized(fromDate: string, outputFile: string) {
const traces = await langfuse.api.traces.list({
fromTimestamp: fromDate,
limit: 1000,
});
const anonymized = traces.data.map(anonymizeTrace);
writeFileSync(outputFile, JSON.stringify(anonymized, null, 2));
}
Data Categories and Retention Category Contains PII? Default Retention Compliance Note Traces (inputs/outputs) Likely 90 days Scrub PII before tracing Generations (LLM I/O) Likely 90 days May contain user data Scores Rarely 1 year Typically safe to retain Sessions User ID linked 90 days Link to user data requests Prompts No Indefinite Template data only Datasets Maybe Per use case Review test data for PII
Error Handling Issue Cause Solution Export timeout Too many traces Reduce date range, use pagination Missing user data Different userId format Verify exact userId used in traces Deletion not immediate Async processing Allow time for propagation Rate limited during export Too many API calls Add 200ms delay between pages
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