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-auth setup
• Node.js 18+ with tsx for 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=${DATABASE_URL}
      - NEXTAUTH_SECRET=${NEXTAUTH_SECRET}
      - NEXTAUTH_URL=http://localhost:3000
      - SALT=${SALT}
      - ENCRYPTION_KEY=${ENCRYPTION_KEY}
    depends_on:
      - db

  db:
    image: postgres:16-alpine
    environment:
      POSTGRES_USER: postgres
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
      POSTGRES_DB: langfuse
    volumes:
      - langfuse-db:/var/lib/postgresql/data

volumes:
  langfuse-db:

Before starting the stack, place unique local-only values for DATABASEURL, POSTGRESPASSWORD, NEXTAUTHSECRET, SALT, and ENCRYPTIONKEY in a git-ignored .env file. Do not commit a database URI or reuse example or production values.

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

Output

Produce a local development receipt naming the SDK/runtime version, local or cloud host, sample trace identifier, and debug setting used. Keep .env.local secret values and local database credentials out of logs and commits.

Examples

Start the watch process, change a prompt or traced function, and verify the reload emits one local trace. For self-hosting, bring up Compose, create a disposable project and key in the local UI, then prove that the application points to localhost rather than cloud.

Resources

• TypeScript SDK Setup
• Self-Hosting Docker Compose
• Advanced SDK Configuration

Next Steps

For SDK patterns and best practices, see langfuse-sdk-patterns.