Langfuse local dev loop
'Set up Langfuse local development workflow with hot reload and debugging.From its SKILL.md
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SKILL.md
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Langfuse Local Dev Loop
Overview
Fast local development workflow with Langfuse tracing, immediate trace visibility, debug logging, and optional self-hosted local instance via Docker.
Prerequisites
- Completed
langfuse-install-authsetup - Node.js 18+ with
tsxfor hot reload (npm install -D tsx) - Docker (optional, for self-hosted local instance)
Instructions
Step 1: Development Environment File
# .env.local (git-ignored)
LANGFUSE_PUBLIC_KEY=pk-lf-dev-...
LANGFUSE_SECRET_KEY=sk-lf-dev-...
LANGFUSE_BASE_URL=https://cloud.langfuse.com
# Dev-specific settings
NODE_ENV=development
OPENAI_API_KEY=sk-...
Step 2: Dev-Optimized Langfuse Setup (v4+)
// src/lib/langfuse-dev.ts
import { LangfuseSpanProcessor } from "@langfuse/otel";
import { NodeSDK } from "@opentelemetry/sdk-node";
import { LangfuseClient } from "@langfuse/client";
const isDev = process.env.NODE_ENV !== "production";
// Configure span processor with dev-friendly settings
const processor = new LangfuseSpanProcessor({
// In dev: flush immediately for instant visibility
...(isDev && { exportIntervalMillis: 1000, maxExportBatchSize: 1 }),
});
const sdk = new NodeSDK({ spanProcessors: [processor] });
sdk.start();
export const langfuse = new LangfuseClient();
// Print trace URLs in development
export function logTrace(traceId: string) {
if (isDev) {
const host = process.env.LANGFUSE_BASE_URL || "https://cloud.langfuse.com";
console.log(`\n Trace: ${host}/trace/${traceId}\n`);
}
}
// Clean shutdown
process.on("SIGINT", async () => {
await sdk.shutdown();
process.exit(0);
});
Step 3: Dev-Optimized Setup (v3 Legacy)
// src/lib/langfuse-dev.ts
import { Langfuse } from "langfuse";
const isDev = process.env.NODE_ENV !== "production";
export const langfuse = new Langfuse({
flushAt: isDev ? 1 : 15, // Immediate flush in dev
flushInterval: isDev ? 1000 : 10000,
...(isDev && { debug: true }), // Verbose SDK logging
});
export function logTraceUrl(trace: ReturnType<typeof langfuse.trace>) {
if (isDev) {
console.log(`\n Trace: ${trace.getTraceUrl()}\n`);
}
}
process.on("beforeExit", async () => {
await langfuse.shutdownAsync();
});
Step 4: Hot Reload Scripts
{
"scripts": {
"dev": "tsx watch --env-file=.env.local src/index.ts",
"dev:debug": "DEBUG=langfuse* tsx watch --env-file=.env.local src/index.ts",
"dev:trace": "LANGFUSE_DEBUG=true tsx watch --env-file=.env.local src/index.ts"
}
}
Step 5: Development Tracing Utilities
// src/lib/dev-utils.ts
import { observe, updateActiveObservation, startActiveObservation } from "@langfuse/tracing";
// Quick traced function wrapper with console output
export function devTrace<T extends (...args: any[]) => Promise<any>>(
name: string,
fn: T
): T {
return observe({ name }, async (...args: Parameters<T>) => {
updateActiveObservation({ input: args, metadata: { env: "dev" } });
const start = Date.now();
const result = await fn(...args);
const duration = Date.now() - start;
updateActiveObservation({ output: result });
console.log(` [${name}] ${duration}ms`);
return result;
}) as T;
}
// Quick debug trace -- fire-and-forget diagnostic trace
export async function debugTrace(name: string, data: Record<string, any>) {
await startActiveObservation(`debug/${name}`, async () => {
updateActiveObservation({
input: data,
metadata: { debug: true, timestamp: new Date().toISOString() },
});
});
}
Step 6: Example Dev Workflow
// src/index.ts
import "dotenv/config";
import { initTracing, langfuse } from "./lib/langfuse-dev";
import { devTrace } from "./lib/dev-utils";
import OpenAI from "openai";
import { observeOpenAI } from "@langfuse/openai";
initTracing();
const openai = observeOpenAI(new OpenAI());
const askQuestion = devTrace("ask-question", async (question: string) => {
const response = await openai.chat.completions.create({
model: "gpt-4o-mini",
messages: [{ role: "user", content: question }],
});
return response.choices[0].message.content;
});
// Run on file save (tsx watch restarts automatically)
const answer = await askQuestion("What is Langfuse?");
console.log("Answer:", answer);
Local Self-Hosted Langfuse (Optional)
For offline development or data privacy:
# docker-compose.langfuse.yml
services:
langfuse:
image: langfuse/langfuse:latest
ports:
- "3000:3000"
environment:
- DATABASE_URL=postgresql://postgres:postgres@db:5432/langfuse
- NEXTAUTH_SECRET=dev-secret-change-in-prod
- NEXTAUTH_URL=http://localhost:3000
- SALT=dev-salt-change-in-prod
- ENCRYPTION_KEY=0000000000000000000000000000000000000000000000000000000000000000
depends_on:
- db
db:
image: postgres:16-alpine
environment:
POSTGRES_USER: postgres
POSTGRES_PASSWORD: postgres
POSTGRES_DB: langfuse
volumes:
- langfuse-db:/var/lib/postgresql/data
volumes:
langfuse-db:
set -euo pipefail
# Start local Langfuse
docker compose -f docker-compose.langfuse.yml up -d
# Wait for startup, then visit http://localhost:3000
# Create account, project, and API keys in the local UI
# Update .env.local
echo 'LANGFUSE_BASE_URL=http://localhost:3000' >> .env.local
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Traces delayed in dev | Batching still active | Set flushAt: 1 or exportIntervalMillis: 1000 |
| No debug output | Debug not enabled | Set LANGFUSE_DEBUG=true or DEBUG=langfuse* |
| Hot reload not working | Wrong watch command | Use tsx watch (not ts-node) |
| Local instance 502 | DB not ready | Wait 10s for PostgreSQL startup |
| Traces going to cloud | Wrong LANGFUSE_BASE_URL | Point to http://localhost:3000 |
Resources
Next Steps
For SDK patterns and best practices, see langfuse-sdk-patterns.
What ships with it
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